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retinal</title> <meta name="description" content="Search results for: all-trans retinal"> <meta name="keywords" content="all-trans retinal"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="all-trans retinal"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 91</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: all-trans retinal</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">91</span> Comparison of Vessel Detection in Standard vs Ultra-WideField Retinal Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maher%20un%20Nisa">Maher un Nisa</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahsan%20Khawaja"> Ahsan Khawaja</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Retinal imaging with Ultra-WideField (UWF) view technology has opened up new avenues in the field of retinal pathology detection. Recent developments in retinal imaging such as Optos California Imaging Device helps in acquiring high resolution images of the retina to help the Ophthalmologists in diagnosing and analyzing eye related pathologies more accurately. This paper investigates the acquired retinal details by comparing vessel detection in standard 450 color fundus images with the state of the art 2000 UWF retinal images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=color%20fundus" title="color fundus">color fundus</a>, <a href="https://publications.waset.org/abstracts/search?q=retinal%20images" title=" retinal images"> retinal images</a>, <a href="https://publications.waset.org/abstracts/search?q=ultra-widefield" title=" ultra-widefield"> ultra-widefield</a>, <a href="https://publications.waset.org/abstracts/search?q=vessel%20detection" title=" vessel detection"> vessel detection</a> </p> <a href="https://publications.waset.org/abstracts/33520/comparison-of-vessel-detection-in-standard-vs-ultra-widefield-retinal-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33520.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">448</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">90</span> Retinal Vascular Tortuosity in Obstructive Sleep Apnea-COPD Overlap Patients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rabab%20A.%20El%20Wahsh">Rabab A. El Wahsh</a>, <a href="https://publications.waset.org/abstracts/search?q=Hatem%20M.%20Marey"> Hatem M. Marey</a>, <a href="https://publications.waset.org/abstracts/search?q=Maha%20Yousif"> Maha Yousif</a>, <a href="https://publications.waset.org/abstracts/search?q=Asmaa%20M.%20Ibrahim"> Asmaa M. Ibrahim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: OSA and COPD are associated with microvascular changes. Retinal microvasculature can be directly and non-invasively examined. Aim: to evaluate retinal vascular tortuosity in patients with COPD, OSA, and overlap syndrome. Subjects and method: Sixty subjects were included; 15 OSA patients, 15 COPD patients, 15 COPD-OSA overlap patients, and 15 matched controls. They underwent digital retinal photography, polysomnography, arterial blood gases, spirometry, ESS, and stop-bang questionnaires. Results: Tortuosity of most retinal vessels was higher in all patient groups compared to the control group; tortuosity was more marked in overlap syndrome. There was a negative correlation between tortuosity of retinal vessels and PO2, O2 saturation, and minimum O2 desaturation, and a positive correlation with PCO2, AHI, O2 desaturation index, BMI and smoking index. Conclusion: Retinal vascular tortuosity occurs in OSA, COPD and overlap syndrome. Retinal vascular tortuosity is correlated with arterial blood gases parameters, polysomnographic findings, smoking index and BMI. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=OSA" title="OSA">OSA</a>, <a href="https://publications.waset.org/abstracts/search?q=COPD" title=" COPD"> COPD</a>, <a href="https://publications.waset.org/abstracts/search?q=overlap%20syndrome" title=" overlap syndrome"> overlap syndrome</a>, <a href="https://publications.waset.org/abstracts/search?q=retinal%20vascular%20tortuosity" title=" retinal vascular tortuosity"> retinal vascular tortuosity</a> </p> <a href="https://publications.waset.org/abstracts/168040/retinal-vascular-tortuosity-in-obstructive-sleep-apnea-copd-overlap-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168040.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">75</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">89</span> Digital Retinal Images: Background and Damaged Areas Segmentation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eman%20A.%20Gani">Eman A. Gani</a>, <a href="https://publications.waset.org/abstracts/search?q=Loay%20E.%20George"> Loay E. George</a>, <a href="https://publications.waset.org/abstracts/search?q=Faisel%20G.%20Mohammed"> Faisel G. Mohammed</a>, <a href="https://publications.waset.org/abstracts/search?q=Kamal%20H.%20Sager"> Kamal H. Sager</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Digital retinal images are more appropriate for automatic screening of diabetic retinopathy systems. Unfortunately, a significant percentage of these images are poor quality that hinders further analysis due to many factors (such as patient movement, inadequate or non-uniform illumination, acquisition angle and retinal pigmentation). The retinal images of poor quality need to be enhanced before the extraction of features and abnormalities. So, the segmentation of retinal image is essential for this purpose, the segmentation is employed to smooth and strengthen image by separating the background and damaged areas from the overall image thus resulting in retinal image enhancement and less processing time. In this paper, methods for segmenting colored retinal image are proposed to improve the quality of retinal image diagnosis. The methods generate two segmentation masks; i.e., background segmentation mask for extracting the background area and poor quality mask for removing the noisy areas from the retinal image. The standard retinal image databases DIARETDB0, DIARETDB1, STARE, DRIVE and some images obtained from ophthalmologists have been used to test the validation of the proposed segmentation technique. Experimental results indicate the introduced methods are effective and can lead to high segmentation accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=retinal%20images" title="retinal images">retinal images</a>, <a href="https://publications.waset.org/abstracts/search?q=fundus%20images" title=" fundus images"> fundus images</a>, <a href="https://publications.waset.org/abstracts/search?q=diabetic%20retinopathy" title=" diabetic retinopathy"> diabetic retinopathy</a>, <a href="https://publications.waset.org/abstracts/search?q=background%20segmentation" title=" background segmentation"> background segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=damaged%20areas%20segmentation" title=" damaged areas segmentation"> damaged areas segmentation</a> </p> <a href="https://publications.waset.org/abstracts/12289/digital-retinal-images-background-and-damaged-areas-segmentation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12289.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">403</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">88</span> Clinical Characteristics of Retinal Detachment Associated with Atopic Dermatitis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hyoung%20Seok%20Kim">Hyoung Seok Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Purpose: To evaluate the clinical characteristics and surgical outcomes of retinal detachment associated with atopic dermatitis. Methods: A retrospective investigation of clinical notes of 37 patients with retinal detachment associated with atopic dermatitis was conducted from January 2019 to December 2023. Initial visual acuity, medical history, type of retinal detachment, number of tears, types of treatment, success rate of treatment, and presence of cataract were investigated. To evaluate the relationship with cataract, the patients were classified into three groups according to lens status: group A (eyes with clear lens), group B (eyes with cataract), and group C (pseudophakic eyes). Results: Of the 37 patients, 29 were male and 8 were female; 10 patients had bilateral retinal detachment (27.0%). The retinal breaks were often located temporally (89.4%), with only 5 cases (10.6%) involving nasal-side retinal breaks. No significant differ ences were noted in the ratio of males to females, age distribution, visual acuity before and after treatments, axial length, and lo cation of retina breaks among the three groups. After primary surgery, retinal detachment recurred in 12 patients (14 eyes), 5 of whom were initially diagnosed with bilateral retinal detachment. In addition, 12 of 14 eyes underwent a second operation, in which detachment recurred in 3 eyes. Conclusions: Incidence of bilateral retinal detachment was high in patients with atopic dermatitis, and the retinal breaks were of ten found on the temporal side. Retinal re-detachment was statistically high in patients with cataract or pseudophakic eyes com pared to patients with clear lens (p = 0.024). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=retinal%20detachment" title="retinal detachment">retinal detachment</a>, <a href="https://publications.waset.org/abstracts/search?q=atopic%20dermatitis" title=" atopic dermatitis"> atopic dermatitis</a>, <a href="https://publications.waset.org/abstracts/search?q=cataract" title=" cataract"> cataract</a>, <a href="https://publications.waset.org/abstracts/search?q=retina%20surgery" title=" retina surgery"> retina surgery</a> </p> <a href="https://publications.waset.org/abstracts/191109/clinical-characteristics-of-retinal-detachment-associated-with-atopic-dermatitis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191109.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">21</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">87</span> 3D Electrode Carrier and its Implications on Retinal Implants</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Diego%20Luj%C3%A1n%20Villarreal">Diego Luján Villarreal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Retinal prosthetic devices aim to repair some vision in visual impairment patients by stimulating electrically neural cells in the visual system. In this study, the 3D linear electrode carrier is presented. A simulation framework was developed by placing the 3D carrier 1 mm away from the fovea center at the highest-density cell. Cell stimulation is verified in COMSOL Multiphysics by developing a 3D computational model which includes the relevant retinal interface elements and dynamics of the voltage-gated ionic channels. Current distribution resulting from low threshold amplitudes produces a small volume equivalent to the volume confined by individual cells at the highest-density cell using small-sized electrodes. Delicate retinal tissue is protected by excessive charge density <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=retinal%20prosthetic%20devices" title="retinal prosthetic devices">retinal prosthetic devices</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20devices" title=" visual devices"> visual devices</a>, <a href="https://publications.waset.org/abstracts/search?q=retinal%20implants." title=" retinal implants."> retinal implants.</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20prosthetic%20devices" title=" visual prosthetic devices"> visual prosthetic devices</a> </p> <a href="https://publications.waset.org/abstracts/162033/3d-electrode-carrier-and-its-implications-on-retinal-implants" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162033.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">113</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">86</span> Retina Registration for Biometrics Based on Characterization of Retinal Feature Points</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nougrara%20Zineb">Nougrara Zineb</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The unique structure of the blood vessels in the retina has been used for biometric identification. The retina blood vessel pattern is a unique pattern in each individual and it is almost impossible to forge that pattern in a false individual. The retina biometrics’ advantages include high distinctiveness, universality, and stability overtime of the blood vessel pattern. Once the creases have been extracted from the images, a registration stage is necessary, since the position of the retinal vessel structure could change between acquisitions due to the movements of the eye. Image registration consists of following steps: Feature detection, feature matching, transform model estimation and image resembling and transformation. In this paper, we present an algorithm of registration; it is based on the characterization of retinal feature points. For experiments, retinal images from the DRIVE database have been tested. The proposed methodology achieves good results for registration in general. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fovea" title="fovea">fovea</a>, <a href="https://publications.waset.org/abstracts/search?q=optic%20disc" title=" optic disc"> optic disc</a>, <a href="https://publications.waset.org/abstracts/search?q=registration" title=" registration"> registration</a>, <a href="https://publications.waset.org/abstracts/search?q=retinal%20images" title=" retinal images"> retinal images</a> </p> <a href="https://publications.waset.org/abstracts/72438/retina-registration-for-biometrics-based-on-characterization-of-retinal-feature-points" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72438.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">266</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">85</span> Visual Outcome After 360-Degree Retinectomy in Total Rhegmatogenous Retinal Detachment with Advanced Proliferative Vitreoretinopathy: A Case Series</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Andriati%20Nadhilah%20Widyarini">Andriati Nadhilah Widyarini</a>, <a href="https://publications.waset.org/abstracts/search?q=Ezra%20Margareth"> Ezra Margareth</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Rhegmatogenous retinal detachment is a condition where there’s a break in the retina, which allows the vitreous to directly enter the subretinal space. Proliferative vitreoretinopathy (PVR) may develop due to this condition and can result in a new break, which could cause traction on the previously detached retina. Various methods of therapy can be done to treat this complication. Case: This case series involved 2 eyes of 2 patients who had total retinal detachment with advanced PVR. Pars plana vitrectomy was performed, and a 360-degree retinectomy procedure with perfluorocarbon liquid usage was done. This was followed by endo laser retinopexy to surround the border of retinectomy. 5000 cs silicone oil was used in 1 eye, whereas 12% of perfluoropropane gas was used in the other eye as a tamponade. These procedures were performed with meticulous attention to prevent any fluid from entering the subretinal space. Postoperative examination showed attachment of the retina and improvement of the patient’s visual acuity. Both eyes’ intraocular pressure was in the normal range. One eye developed retinal displacement, but no other complications occurred. Discussion: Rhegmatogenous retinal detachment with advanced PVR is a complex situation for vitreoretinal surgeons. PVR is characterized by the growth and migration of preretinal or subretinal membranes. PVR is the most common cause of retinal reattachment failure. A 360-degree retinectomy is an alternative surgical method to overcome this condition. Objectives of this procedure are releasing retinal traction caused by PVR, reducing the recurrence rate of PVR, and reattaching the retina to the pigment epithelial surface. Conclusion: 360-degree retinectomy provides satisfactory retinal reattachment and visual outcome improvement in rhegmatogenous retinal detachment with advanced PVR. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=RRD" title="RRD">RRD</a>, <a href="https://publications.waset.org/abstracts/search?q=retinectomy" title=" retinectomy"> retinectomy</a>, <a href="https://publications.waset.org/abstracts/search?q=pars%20plana" title=" pars plana"> pars plana</a>, <a href="https://publications.waset.org/abstracts/search?q=advanced%20PVR" title=" advanced PVR"> advanced PVR</a> </p> <a href="https://publications.waset.org/abstracts/181173/visual-outcome-after-360-degree-retinectomy-in-total-rhegmatogenous-retinal-detachment-with-advanced-proliferative-vitreoretinopathy-a-case-series" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/181173.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">47</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">84</span> Comparison of Central Light Reflex Width-to-Retinal Vessel Diameter Ratio between Glaucoma and Normal Eyes by Using Edge Detection Technique </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20Siriarchawatana">P. Siriarchawatana</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Leungchavaphongse"> K. Leungchavaphongse</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Covavisaruch"> N. Covavisaruch</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Rojananuangnit"> K. Rojananuangnit</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Boondaeng"> P. Boondaeng</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Panyayingyong"> N. Panyayingyong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Glaucoma is a disease that causes visual loss in adults. Glaucoma causes damage to the optic nerve and its overall pathophysiology is still not fully understood. Vasculopathy may be one of the possible causes of nerve damage. Photographic imaging of retinal vessels by fundus camera during eye examination may complement clinical management. This paper presents an innovation for measuring central light reflex width-to-retinal vessel diameter ratio (CRR) from digital retinal photographs. Using our edge detection technique, CRRs from glaucoma and normal eyes were compared to examine differences and associations. CRRs were evaluated on fundus photographs of participants from Mettapracharak (Wat Raikhing) Hospital in Nakhon Pathom, Thailand. Fifty-five photographs from normal eyes and twenty-one photographs from glaucoma eyes were included. Participants with hypertension were excluded. In each photograph, CRRs from four retinal vessels, including arteries and veins in the inferotemporal and superotemporal regions, were quantified using edge detection technique. From our finding, mean CRRs of all four retinal arteries and veins were significantly higher in persons with glaucoma than in those without glaucoma (0.34 <em>vs</em>. 0.32, <em>p</em> < 0.05 for inferotemporal vein, 0.33 <em>vs</em>. 0.30, <em>p</em> < 0.01 for inferotemporal artery, 0.34 <em>vs</em>. 0.31, <em>p </em>< 0.01 for superotemporal vein, and 0.33 <em>vs</em>. 0.30, <em>p</em> < 0.05 for superotemporal artery). From these results, an increase in CRRs of retinal vessels, as quantitatively measured from fundus photographs, could be associated with glaucoma. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=glaucoma" title="glaucoma">glaucoma</a>, <a href="https://publications.waset.org/abstracts/search?q=retinal%20vessel" title=" retinal vessel"> retinal vessel</a>, <a href="https://publications.waset.org/abstracts/search?q=central%20light%20reflex" title=" central light reflex"> central light reflex</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=fundus%20photograph" title=" fundus photograph"> fundus photograph</a>, <a href="https://publications.waset.org/abstracts/search?q=edge%20detection" title=" edge detection"> edge detection</a> </p> <a href="https://publications.waset.org/abstracts/54545/comparison-of-central-light-reflex-width-to-retinal-vessel-diameter-ratio-between-glaucoma-and-normal-eyes-by-using-edge-detection-technique" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54545.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">325</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">83</span> Retinal Changes in Patients with Idiopathic Inflammatory Myopathies: A Case-Control Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rachna%20Agarwal">Rachna Agarwal</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Naveen"> R. Naveen</a>, <a href="https://publications.waset.org/abstracts/search?q=Darpan%20Thakre"> Darpan Thakre</a>, <a href="https://publications.waset.org/abstracts/search?q=Rohit%20Shahi"> Rohit Shahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Maryam%20Abbasi"> Maryam Abbasi</a>, <a href="https://publications.waset.org/abstracts/search?q=Upendra%20Rathore"> Upendra Rathore</a>, <a href="https://publications.waset.org/abstracts/search?q=Latika%20Gupta"> Latika Gupta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Aim: Retinal changes are the window to systemic vasculature. Therefore, we explored retinal changes in patients with idiopathic inflammatory myopathies (IIM) as a surrogate for vascular health. Methods: Adult and juvenile IIM patients visiting a tertiary care centre in 2021 satisfying the International Myositis Classification Criteria were enrolled for detailed ophthalmic examination in comparison with healthy controls (HC). Patients with conditions that precluded thorough posterior chamber examination were excluded. Scale variables are expressed as median (IQR). Multivariate analysis (binary logistic regression-BLR) was conducted, adjusting for age, gender, and comorbidities besides factors significant in univariate analysis. Results: 43 patients with IIM [31 females; age 36 (23-45) years; disease duration 5.5 (2-12) months] were enrolled for participation. DM (44%) was the most common diagnosis. IIM patients exhibited frequent attenuation of retinal vessels (32.6% vs. 4.3%, p <0.001), AV nicking (14% vs. 2.2%, p=0.053), and vascular tortuosity (18.6% vs. 2.2%, p=0.012), besides decreased visual acuity (53.5% vs. 10.9%, p<0.001) and immature cataracts (34.9% vs. 2.2%, p<0.001). Attenuation of vessels [OR 10.9 (1.7-71), p=0.004] emerged as significantly different from HC after adjusting for covariates in BLR. Notably, adults with IIM were more predisposed to retinal abnormalities [21 (57%) vs. 1 (16%), p=0.068], especially attenuation of vessels [14(38%) vs. 0(0), p=0.067] than jIIM. However, no difference was found in retinal features amongst the subtypes of adult IIM, nor did they correlate with MDAAT, MDI, or HAQ-DI. Conclusion: Retinal microvasculopathy and diminution of vision occur in nearly one-third to half of the patients with IIM. Microvasculopathy occurs across subtypes of IIM, and more so in adults, calling for further investigation as a surrogate for damage assessment and potentially even systemic vascular health. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=idiopathic%20inflammatory%20myopathies" title="idiopathic inflammatory myopathies">idiopathic inflammatory myopathies</a>, <a href="https://publications.waset.org/abstracts/search?q=vascular%20health" title=" vascular health"> vascular health</a>, <a href="https://publications.waset.org/abstracts/search?q=retinal%20microvasculopathy" title=" retinal microvasculopathy"> retinal microvasculopathy</a>, <a href="https://publications.waset.org/abstracts/search?q=arterial%20attenuation" title=" arterial attenuation"> arterial attenuation</a> </p> <a href="https://publications.waset.org/abstracts/159817/retinal-changes-in-patients-with-idiopathic-inflammatory-myopathies-a-case-control-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159817.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">91</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">82</span> Surgical Outcome of Heavy Silicone Oil in Rhegmatogenous Retinal Detachment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pheeraphat%20Ussadamongkol">Pheeraphat Ussadamongkol</a>, <a href="https://publications.waset.org/abstracts/search?q=Suthasinee%20Sinawat"> Suthasinee Sinawat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Objective: The purpose of this study is to evaluate the anatomical and visual outcomes associated with the use of heavy silicone oil (HSO) during pars plana vitrectomy (PPV) in patients with rhegmatogenous retinal detachment (RRD). Materials and methods: A Total of 66 eyes of 66 patients with RRD patients who underwent PPV with HSO from 2018-2023 were included in this retrospective study. Risk factors of surgical outcomes were also investigated. Results: The mean age of the recruited patients was 55.26 ± 13.05 years. The most common diagnosis was recurrent RRD, with 43 patients (65.15%), and the majority of these patients (81.39%) had a history of multiple vitreoretinal surgeries. Inferior breaks and PVR grade ≧ C were present in 65.15% and 42.42% of cases, respectively. The mean duration of HSO tamponade was 7.77+5.19 months. The retinal attachment rate after surgery was 71.21%, with a final attachment rate of 87.88%. The mean final VA was 1.62 ± 1.11 logMAR. 54.54% of patients could achieve a final visual acuity (VA)  6/60. Multivariate analysis revealed that proliferative vitreoretinopathy (PVR) and multiple breaks were significantly associated with retinal redetachment, while initial good VA (  6/60) was associated with good visual outcome ( 6/60). The most common complications were glaucoma (30.3%) and epimacular membrane (7.58%). Conclusion: The use of heavy silicone oil in pars plana vitrectomy for rhegmatogenous retinal detachment yields favorable anatomical and visual outcomes. Factors associated with retinal redetachment are proliferative vitreoretinopathy and multiple breaks. Good initial VA can predict good visual outcomes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=rhegmatogenous%20retinal%20detachment" title="rhegmatogenous retinal detachment">rhegmatogenous retinal detachment</a>, <a href="https://publications.waset.org/abstracts/search?q=heavy%20silicone%20oil" title=" heavy silicone oil"> heavy silicone oil</a>, <a href="https://publications.waset.org/abstracts/search?q=surgical%20outcome" title=" surgical outcome"> surgical outcome</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20outcome" title=" visual outcome"> visual outcome</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20factors" title=" risk factors"> risk factors</a> </p> <a href="https://publications.waset.org/abstracts/194417/surgical-outcome-of-heavy-silicone-oil-in-rhegmatogenous-retinal-detachment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/194417.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">7</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">81</span> Morphology Operation and Discrete Wavelet Transform for Blood Vessels Segmentation in Retina Fundus</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rita%20Magdalena">Rita Magdalena</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20K.%20Caecar%20Pratiwi"> N. K. Caecar Pratiwi</a>, <a href="https://publications.waset.org/abstracts/search?q=Yunendah%20Nur%20Fuadah"> Yunendah Nur Fuadah</a>, <a href="https://publications.waset.org/abstracts/search?q=Sofia%20Saidah"> Sofia Saidah</a>, <a href="https://publications.waset.org/abstracts/search?q=Bima%20Sakti"> Bima Sakti</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Vessel segmentation of retinal fundus is important for biomedical sciences in diagnosing ailments related to the eye. Segmentation can simplify medical experts in diagnosing retinal fundus image state. Therefore, in this study, we designed a software using MATLAB which enables the segmentation of the retinal blood vessels on retinal fundus images. There are two main steps in the process of segmentation. The first step is image preprocessing that aims to improve the quality of the image to be optimum segmented. The second step is the image segmentation in order to perform the extraction process to retrieve the retina’s blood vessel from the eye fundus image. The image segmentation methods that will be analyzed in this study are Morphology Operation, Discrete Wavelet Transform and combination of both. The amount of data that used in this project is 40 for the retinal image and 40 for manually segmentation image. After doing some testing scenarios, the average accuracy for Morphology Operation method is 88.46 % while for Discrete Wavelet Transform is 89.28 %. By combining the two methods mentioned in later, the average accuracy was increased to 89.53 %. The result of this study is an image processing system that can segment the blood vessels in retinal fundus with high accuracy and low computation time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=discrete%20wavelet%20transform" title="discrete wavelet transform">discrete wavelet transform</a>, <a href="https://publications.waset.org/abstracts/search?q=fundus%20retina" title=" fundus retina"> fundus retina</a>, <a href="https://publications.waset.org/abstracts/search?q=morphology%20operation" title=" morphology operation"> morphology operation</a>, <a href="https://publications.waset.org/abstracts/search?q=segmentation" title=" segmentation"> segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=vessel" title=" vessel"> vessel</a> </p> <a href="https://publications.waset.org/abstracts/105620/morphology-operation-and-discrete-wavelet-transform-for-blood-vessels-segmentation-in-retina-fundus" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/105620.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">195</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">80</span> A Multilevel Approach for Stroke Prediction Combining Risk Factors and Retinal Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jeena%20R.%20S.">Jeena R. S.</a>, <a href="https://publications.waset.org/abstracts/search?q=Sukesh%20Kumar%20A."> Sukesh Kumar A.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Stroke is one of the major reasons of adult disability and morbidity in many of the developing countries like India. Early diagnosis of stroke is essential for timely prevention and cure. Various conventional statistical methods and computational intelligent models have been developed for predicting the risk and outcome of stroke. This research work focuses on a multilevel approach for predicting the occurrence of stroke based on various risk factors and invasive techniques like retinal imaging. This risk prediction model can aid in clinical decision making and help patients to have an improved and reliable risk prediction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=prediction" title="prediction">prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=retinal%20imaging" title=" retinal imaging"> retinal imaging</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20factors" title=" risk factors"> risk factors</a>, <a href="https://publications.waset.org/abstracts/search?q=stroke" title=" stroke"> stroke</a> </p> <a href="https://publications.waset.org/abstracts/91133/a-multilevel-approach-for-stroke-prediction-combining-risk-factors-and-retinal-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/91133.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">303</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">79</span> The Retinoprotective Effects and Mechanisms of Fungal Ingredient 3,4-Dihydroxybenzalacetone through Inhibition of Retinal Müller and Microglial Activation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yu-Wen%20Cheng">Yu-Wen Cheng</a>, <a href="https://publications.waset.org/abstracts/search?q=Jau-Der%20Ho"> Jau-Der Ho</a>, <a href="https://publications.waset.org/abstracts/search?q=Liang-Huan%20Wu"> Liang-Huan Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Fan-Li%20Lin"> Fan-Li Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Li-Huei%20Chen"> Li-Huei Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Hung-Ming%20Chang"> Hung-Ming Chang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yueh-Hsiung%20Kuo"> Yueh-Hsiung Kuo</a>, <a href="https://publications.waset.org/abstracts/search?q=George%20Hsiao"> George Hsiao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Retina glial activation and neuroinflammation have been confirmed to cause devastating responses in retinodegenerative diseases. The expression and activation of matrix metalloproteinase (MMP)-9 and inducible nitric oxide synthase (iNOS) could be exerted as the crucial pathological factors in glaucoma- and blue light-induced retinal injuries. The present study aimed to investigate the retinoprotective effects and mechanisms of fungal ingredient 3,4-dihydroxybenzalacetone (DBL) isolated from Phellinus linteus in the retinal glial activation and retinodegenerative animal models. According to the cellular studies, DBL significantly and concentration-dependently abrogated MMP-9 activation and expression in TNFα-stimulated retinal Müller (rMC-1) cells. We found the inhibitory activities of DBL were strongly through the STAT- and ERK-dependent pathways. Furthermore, DBL dramatically attenuated MMP-9 activation in the stimulated Müller cells exposed to conditioned media from LPS-stimulated microglia BV-2 cells. On the other hand, DBL strongly suppressed LPS-induced production of NO and ROS and expression of iNOS in microglia BV-2 cells. Consistently, the phosphorylation of STAT was substantially blocked by DBL in LPS-stimulated microglia BV-2 cells. In the evaluation of retinoprotective functions, the high IOP-induced scotopic electroretinographic (ERG) deficit and blue light-induced abnormal pupillary light response (PLR) were assessed. The deficit scotopic ERG responses markedly recovered by DBL in a rat model of glaucoma-like ischemia/reperfusion (I/R)-injury. DBL also reduced the aqueous gelatinolytic activity and retinal MMP-9 expression in high IOP-injured conditions. Additionally, DBL could restore the abnormal PLR and reduce retinal MMP-9 activation. In summary, DBL could ameliorate retinal neuroinflammation and MMP-9 activation by predominantly inhibiting STAT3 activation in the retinal Müller cells and microglia, which exhibits therapeutic potential for glaucoma and other retinal degenerative diseases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=glaucoma" title="glaucoma">glaucoma</a>, <a href="https://publications.waset.org/abstracts/search?q=blue%20light" title=" blue light"> blue light</a>, <a href="https://publications.waset.org/abstracts/search?q=DBL" title=" DBL"> DBL</a>, <a href="https://publications.waset.org/abstracts/search?q=retinal%20M%C3%BCller%20cell" title=" retinal Müller cell"> retinal Müller cell</a>, <a href="https://publications.waset.org/abstracts/search?q=MMP-9" title=" MMP-9"> MMP-9</a>, <a href="https://publications.waset.org/abstracts/search?q=STAT" title=" STAT"> STAT</a>, <a href="https://publications.waset.org/abstracts/search?q=Microglia" title=" Microglia"> Microglia</a>, <a href="https://publications.waset.org/abstracts/search?q=iNOS" title=" iNOS"> iNOS</a>, <a href="https://publications.waset.org/abstracts/search?q=ERG" title=" ERG"> ERG</a>, <a href="https://publications.waset.org/abstracts/search?q=PLR" title=" PLR"> PLR</a> </p> <a href="https://publications.waset.org/abstracts/136717/the-retinoprotective-effects-and-mechanisms-of-fungal-ingredient-34-dihydroxybenzalacetone-through-inhibition-of-retinal-muller-and-microglial-activation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/136717.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">139</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">78</span> A Virtual Electrode through Summation of Time Offset Pulses</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Isaac%20Cassar">Isaac Cassar</a>, <a href="https://publications.waset.org/abstracts/search?q=Trevor%20Davis"> Trevor Davis</a>, <a href="https://publications.waset.org/abstracts/search?q=Yi-Kai%20Lo"> Yi-Kai Lo</a>, <a href="https://publications.waset.org/abstracts/search?q=Wentai%20Liu"> Wentai Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Retinal prostheses have been successful in eliciting visual responses in implanted subjects. As these prostheses progress, one of their major limitations is the need for increased resolution. As an alternative to increasing the number of electrodes, virtual electrodes may be used to increase the effective resolution of current electrode arrays. This paper presents a virtual electrode technique based upon time-offsets between stimuli. Two adjacent electrodes are stimulated with identical pulses with too short of pulse widths to activate a neuron, but one has a time offset of one pulse width. A virtual electrode of twice the pulse width was then shown to appear in the center, with a total width capable of activating a neuron. This can be used in retinal implants by stimulating electrodes with pulse widths short enough to not elicit responses in neurons, but with their combined pulse width adequate to activate a neuron in between them. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electrical%20stimulation" title="electrical stimulation">electrical stimulation</a>, <a href="https://publications.waset.org/abstracts/search?q=neuroprosthesis" title=" neuroprosthesis"> neuroprosthesis</a>, <a href="https://publications.waset.org/abstracts/search?q=retinal%20implant" title=" retinal implant"> retinal implant</a>, <a href="https://publications.waset.org/abstracts/search?q=retinal%20prosthesis" title=" retinal prosthesis"> retinal prosthesis</a>, <a href="https://publications.waset.org/abstracts/search?q=virtual%20electrode" title=" virtual electrode"> virtual electrode</a> </p> <a href="https://publications.waset.org/abstracts/14443/a-virtual-electrode-through-summation-of-time-offset-pulses" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14443.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">303</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">77</span> Automatic Detection and Classification of Diabetic Retinopathy Using Retinal Fundus Images </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Biran">A. Biran</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Sobhe%20Bidari"> P. Sobhe Bidari</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Almazroe"> A. Almazroe</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20Lakshminarayanan"> V. Lakshminarayanan</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Raahemifar"> K. Raahemifar </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=diabetic%20retinopathy" title="diabetic retinopathy">diabetic retinopathy</a>, <a href="https://publications.waset.org/abstracts/search?q=fundus%20images" title=" fundus images"> fundus images</a>, <a href="https://publications.waset.org/abstracts/search?q=STARE" title=" STARE"> STARE</a>, <a href="https://publications.waset.org/abstracts/search?q=Gabor%20filter" title=" Gabor filter"> Gabor filter</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a> </p> <a href="https://publications.waset.org/abstracts/49824/automatic-detection-and-classification-of-diabetic-retinopathy-using-retinal-fundus-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49824.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">294</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">76</span> Excited State Structural Dynamics of Retinal Isomerization Revealed by a Femtosecond X-Ray Laser </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Przemyslaw%20Nogly">Przemyslaw Nogly</a>, <a href="https://publications.waset.org/abstracts/search?q=Tobias%20Weinert"> Tobias Weinert</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniel%20James"> Daniel James</a>, <a href="https://publications.waset.org/abstracts/search?q=Sergio%20Carbajo"> Sergio Carbajo</a>, <a href="https://publications.waset.org/abstracts/search?q=Dmitry%20Ozerov"> Dmitry Ozerov</a>, <a href="https://publications.waset.org/abstracts/search?q=Antonia%20Furrer"> Antonia Furrer</a>, <a href="https://publications.waset.org/abstracts/search?q=Dardan%20Gashi"> Dardan Gashi</a>, <a href="https://publications.waset.org/abstracts/search?q=Veniamin%20Borin"> Veniamin Borin</a>, <a href="https://publications.waset.org/abstracts/search?q=Petr%20Skopintsev"> Petr Skopintsev</a>, <a href="https://publications.waset.org/abstracts/search?q=Kathrin%20Jaeger"> Kathrin Jaeger</a>, <a href="https://publications.waset.org/abstracts/search?q=Karol%20Nass"> Karol Nass</a>, <a href="https://publications.waset.org/abstracts/search?q=Petra%20Bath"> Petra Bath</a>, <a href="https://publications.waset.org/abstracts/search?q=Robert%20Bosman"> Robert Bosman</a>, <a href="https://publications.waset.org/abstracts/search?q=Jason%20Koglin"> Jason Koglin</a>, <a href="https://publications.waset.org/abstracts/search?q=Matthew%20Seaberg"> Matthew Seaberg</a>, <a href="https://publications.waset.org/abstracts/search?q=Thomas%20Lane"> Thomas Lane</a>, <a href="https://publications.waset.org/abstracts/search?q=Demet%20Kekilli"> Demet Kekilli</a>, <a href="https://publications.waset.org/abstracts/search?q=Steffen%20Br%C3%BCnle"> Steffen Brünle</a>, <a href="https://publications.waset.org/abstracts/search?q=Tomoyuki%20Tanaka"> Tomoyuki Tanaka</a>, <a href="https://publications.waset.org/abstracts/search?q=Wenting%20Wu"> Wenting Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Christopher%20Milne"> Christopher Milne</a>, <a href="https://publications.waset.org/abstracts/search?q=Thomas%20A.%20White"> Thomas A. White</a>, <a href="https://publications.waset.org/abstracts/search?q=Anton%20Barty"> Anton Barty</a>, <a href="https://publications.waset.org/abstracts/search?q=Uwe%20Weierstall"> Uwe Weierstall</a>, <a href="https://publications.waset.org/abstracts/search?q=Valerie%20Panneels"> Valerie Panneels</a>, <a href="https://publications.waset.org/abstracts/search?q=Eriko%20Nango"> Eriko Nango</a>, <a href="https://publications.waset.org/abstracts/search?q=So%20Iwata"> So Iwata</a>, <a href="https://publications.waset.org/abstracts/search?q=Mark%20Hunter"> Mark Hunter</a>, <a href="https://publications.waset.org/abstracts/search?q=Igor%20Schapiro"> Igor Schapiro</a>, <a href="https://publications.waset.org/abstracts/search?q=Gebhard%20Schertler"> Gebhard Schertler</a>, <a href="https://publications.waset.org/abstracts/search?q=Richard%20Neutze"> Richard Neutze</a>, <a href="https://publications.waset.org/abstracts/search?q=J%C3%B6rg%20Standfuss"> Jörg Standfuss</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ultrafast isomerization of retinal is the primary step in a range of photoresponsive biological functions including vision in humans and ion-transport across bacterial membranes. We studied the sub-picosecond structural dynamics of retinal isomerization in the light-driven proton pump bacteriorhodopsin using an X-ray laser. Twenty snapshots with near-atomic spatial and temporal resolution in the femtosecond regime show how the excited all-trans retinal samples conformational states within the protein binding pocket prior to passing through a highly-twisted geometry and emerging in the 13-cis conformation. The aspartic acid residues and functional water molecules in proximity of the retinal Schiff base respond collectively to formation and decay of the initial excited state and retinal isomerization. These observations reveal how the protein scaffold guides this remarkably efficient photochemical reaction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bacteriorhodopsin" title="bacteriorhodopsin">bacteriorhodopsin</a>, <a href="https://publications.waset.org/abstracts/search?q=free-electron%20laser" title=" free-electron laser"> free-electron laser</a>, <a href="https://publications.waset.org/abstracts/search?q=retinal%20isomerization%20mechanism" title=" retinal isomerization mechanism"> retinal isomerization mechanism</a>, <a href="https://publications.waset.org/abstracts/search?q=time-resolved%20crystallography" title=" time-resolved crystallography"> time-resolved crystallography</a> </p> <a href="https://publications.waset.org/abstracts/90555/excited-state-structural-dynamics-of-retinal-isomerization-revealed-by-a-femtosecond-x-ray-laser" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/90555.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">248</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">75</span> Generative Adversarial Network for Bidirectional Mappings between Retinal Fundus Images and Vessel Segmented Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Haoqi%20Gao">Haoqi Gao</a>, <a href="https://publications.waset.org/abstracts/search?q=Koichi%20Ogawara"> Koichi Ogawara</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Retinal vascular segmentation of color fundus is the basis of ophthalmic computer-aided diagnosis and large-scale disease screening systems. Early screening of fundus diseases has great value for clinical medical diagnosis. The traditional methods depend on the experience of the doctor, which is time-consuming, labor-intensive, and inefficient. Furthermore, medical images are scarce and fraught with legal concerns regarding patient privacy. In this paper, we propose a new Generative Adversarial Network based on CycleGAN for retinal fundus images. This method can generate not only synthetic fundus images but also generate corresponding segmentation masks, which has certain application value and challenge in computer vision and computer graphics. In the results, we evaluate our proposed method from both quantitative and qualitative. For generated segmented images, our method achieves dice coefficient of 0.81 and PR of 0.89 on DRIVE dataset. For generated synthetic fundus images, we use ”Toy Experiment” to verify the state-of-the-art performance of our method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=retinal%20vascular%20segmentations" title="retinal vascular segmentations">retinal vascular segmentations</a>, <a href="https://publications.waset.org/abstracts/search?q=generative%20ad-versarial%20network" title=" generative ad-versarial network"> generative ad-versarial network</a>, <a href="https://publications.waset.org/abstracts/search?q=cyclegan" title=" cyclegan"> cyclegan</a>, <a href="https://publications.waset.org/abstracts/search?q=fundus%20images" title=" fundus images"> fundus images</a> </p> <a href="https://publications.waset.org/abstracts/110591/generative-adversarial-network-for-bidirectional-mappings-between-retinal-fundus-images-and-vessel-segmented-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110591.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">144</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">74</span> Enhancing the Bionic Eye: A Real-time Image Optimization Framework to Encode Color and Spatial Information Into Retinal Prostheses</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=William%20Huang">William Huang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Retinal prostheses are currently limited to low resolution grayscale images that lack color and spatial information. This study develops a novel real-time image optimization framework and tools to encode maximum information to the prostheses which are constrained by the number of electrodes. One key idea is to localize main objects in images while reducing unnecessary background noise through region-contrast saliency maps. A novel color depth mapping technique was developed through MiniBatchKmeans clustering and color space selection. The resulting image was downsampled using bicubic interpolation to reduce image size while preserving color quality. In comparison to current schemes, the proposed framework demonstrated better visual quality in tested images. The use of the region-contrast saliency map showed improvements in efficacy up to 30%. Finally, the computational speed of this algorithm is less than 380 ms on tested cases, making real-time retinal prostheses feasible. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=retinal%20implants" title="retinal implants">retinal implants</a>, <a href="https://publications.waset.org/abstracts/search?q=virtual%20processing%20unit" title=" virtual processing unit"> virtual processing unit</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20vision" title=" computer vision"> computer vision</a>, <a href="https://publications.waset.org/abstracts/search?q=saliency%20maps" title=" saliency maps"> saliency maps</a>, <a href="https://publications.waset.org/abstracts/search?q=color%20quantization" title=" color quantization"> color quantization</a> </p> <a href="https://publications.waset.org/abstracts/147972/enhancing-the-bionic-eye-a-real-time-image-optimization-framework-to-encode-color-and-spatial-information-into-retinal-prostheses" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147972.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">153</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">73</span> Large-Capacity Image Information Reduction Based on Single-Cue Saliency Map for Retinal Prosthesis System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yili%20Chen">Yili Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaokun%20Liang"> Xiaokun Liang</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhicheng%20Zhang"> Zhicheng Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yaoqin%20Xie"> Yaoqin Xie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In an effort to restore visual perception in retinal diseases, an electronic retinal prosthesis with thousands of electrodes has been developed. The image processing strategies of retinal prosthesis system converts the original images from the camera to the stimulus pattern which can be interpreted by the brain. Practically, the original images are with more high resolution (256x256) than that of the stimulus pattern (such as 25x25), which causes a technical image processing challenge to do large-capacity image information reduction. In this paper, we focus on developing an efficient image processing stimulus pattern extraction algorithm by using a single cue saliency map for extracting salient objects in the image with an optimal trimming threshold. Experimental results showed that the proposed stimulus pattern extraction algorithm performs quite well for different scenes in terms of the stimulus pattern. In the algorithm performance experiment, our proposed SCSPE algorithm have almost five times of the score compared with Boyle’s algorithm. Through experiment s we suggested that when there are salient objects in the scene (such as the blind meet people or talking with people), the trimming threshold should be set around 0.4max, in other situations, the trimming threshold values can be set between 0.2max-0.4max to give the satisfied stimulus pattern. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=retinal%20prosthesis" title="retinal prosthesis">retinal prosthesis</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=region%20of%20interest" title=" region of interest"> region of interest</a>, <a href="https://publications.waset.org/abstracts/search?q=saliency%20map" title=" saliency map"> saliency map</a>, <a href="https://publications.waset.org/abstracts/search?q=trimming%20threshold%20selection" title=" trimming threshold selection"> trimming threshold selection</a> </p> <a href="https://publications.waset.org/abstracts/36987/large-capacity-image-information-reduction-based-on-single-cue-saliency-map-for-retinal-prosthesis-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/36987.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">246</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">72</span> Inhibition of Glutamate Carboxypeptidase Activity Protects Retinal Ganglionic Cell Death Induced by Ischemia-Reperfusion by Reducing the Astroglial Activation in Rat</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dugeree%20Otgongerel">Dugeree Otgongerel</a>, <a href="https://publications.waset.org/abstracts/search?q=Kyong%20Jin%20Cho"> Kyong Jin Cho</a>, <a href="https://publications.waset.org/abstracts/search?q=Yu-Han%20Kim"> Yu-Han Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Sangmee%20Ahn%20Jo"> Sangmee Ahn Jo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Excessive activation of glutamate receptor is thought to be involved in retinal ganglion cell (RGC) death after ischemia- reperfusion damage. Glutamate carboxypeptidase II (GCPII) is an enzyme responsible for the synthesis of glutamate. Several studies showed that inhibition of GCPII prevents or reduces cellular damage in brain diseases. Thus, in this study, we examined the expression of GCPII in rat retina and the role of GCPII in acute high IOP ischemia-reperfusion damage of eye by using a GCPII inhibitor, 2-(phosphonomethyl) pentanedioic acid (2-PMPA). Animal model of ischemia-reperfusion was induced by raising the intraocular pressure for 60 min and followed by reperfusion for 3 days. Rats were randomly divided into four groups: either intra-vitreous injection of 2-PMPA (11 or 110 ng per eye) or PBS after ischemia-reperfusion, 2-PMPA treatment without ischemia-reperfusion and sham-operated normal control. GCPII immunoreactivity in normal rat retina was detected weakly in retinal nerve fiber layer (RNFL) and retinal ganglionic cell layer (RGL) and also inner plexiform layer (IPL) and outer plexiform layer (OPL) strongly where are co-stained with an anti-GFAP antibody, suggesting that GCPII is expressed mostly in Muller and astrocytes. Immunostaining with anti-BRN antibody showed that ischemia- reperfusion caused RGC death (31.5 %) and decreased retinal thickness in all layers of damaged retina, but the treatment of 2-PMPA twice at 0 and 48 hour after reperfusion blocked these retinal damages. GCPII level in RNFL layer was enhanced after ischemia-reperfusion but was blocked by PMPA treatment. This result was confirmed by western blot analysis showing that the level of GCPII protein after ischemia- reperfusion increased by 2.2- fold compared to control, but this increase was blocked almost completely by 110 ng PMPA treatment. Interestingly, GFAP immunoreactivity in the retina after ischemia- reperfusion followed by treatment with PMPA showed similar pattern to GCPII, increase after ischemia-reperfusion but reduction to the normal level by PMPA treatment. Our data demonstrate that increase of GCPII protein level after ischemia-reperfusion injury is likely to cause glial activation and/or retinal cell death which are mediated by glutamate, and GCPII inhibitors may be useful in treatment of retinal disorders in which glutamate excitotoxicity is pathogenic. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=glutamate%20carboxypepptidase%20II" title="glutamate carboxypepptidase II">glutamate carboxypepptidase II</a>, <a href="https://publications.waset.org/abstracts/search?q=glutamate%20excitotoxicity" title=" glutamate excitotoxicity"> glutamate excitotoxicity</a>, <a href="https://publications.waset.org/abstracts/search?q=ischemia-reperfusion" title=" ischemia-reperfusion"> ischemia-reperfusion</a>, <a href="https://publications.waset.org/abstracts/search?q=retinal%20ganglion%20cell" title=" retinal ganglion cell"> retinal ganglion cell</a> </p> <a href="https://publications.waset.org/abstracts/39644/inhibition-of-glutamate-carboxypeptidase-activity-protects-retinal-ganglionic-cell-death-induced-by-ischemia-reperfusion-by-reducing-the-astroglial-activation-in-rat" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39644.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">340</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">71</span> Comparison of Early Silicon Oil Removal and Late Silicon Oil Removal in Patients With Rhegmatogenous Retinal Detachment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamidreza%20Torabi">Hamidreza Torabi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohsen%20Moghtaderi"> Mohsen Moghtaderi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Currently, deep vitrectomy with silicone oil tamponade is the standard treatment method for patients with Rhegmatogenous Retinal Detachment (RRD). After retinal repair, it is necessary to remove silicone oil from the eye, but the appropriate time to remove the oil and complications related to that time has been less studied. The aim of this study was to compare the results of the early removal of silicone oil with the delayed removal of silicone oil in patients with RRD. Method & material: Patients who were referred to the Ophthalmology Clinic of Baqiyatallah Hospital, Tehran, Iran, due to RRD with detached macula in 2021 & 2022 were evaluated. These patients were treated with deep vitrectomy and silicone oil tamponade. Patients whose retinas were attached after the passage of time were candidates for silicone oil removal (SOR) surgery. For patients in the early SOR group, SOR surgery was performed 3-6 months after the initial vitrectomy surgery, and for the late SOR group, SOR was performed after 6 months after the initial vitrectomy surgery. Results: In this study, 60 patients with RRD were evaluated. 23 (38.3%) patients were in the early group, and 37 (61.7%) patients were in the late group. Based on our findings, it was seen that the mean visual acuity of patients based on the Snellen chart in the early group (0.48 ± 0.23 Decimal) was better than the late group (0.33 ± 0.18 Decimal) (P-value=0.009). Retinal re-detachment has happened only in one patient with early SOR. Conclusion: Early removal of silicone oil (less than 6 months) from the eyes of patients undergoing RRD surgery has been associated with better vision results compared to late removal. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=retinal%20detachment" title="retinal detachment">retinal detachment</a>, <a href="https://publications.waset.org/abstracts/search?q=vitrectomy" title=" vitrectomy"> vitrectomy</a>, <a href="https://publications.waset.org/abstracts/search?q=silicone%20oil" title=" silicone oil"> silicone oil</a>, <a href="https://publications.waset.org/abstracts/search?q=silicone%20oil%20removal" title=" silicone oil removal"> silicone oil removal</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20acuity" title=" visual acuity"> visual acuity</a> </p> <a href="https://publications.waset.org/abstracts/165024/comparison-of-early-silicon-oil-removal-and-late-silicon-oil-removal-in-patients-with-rhegmatogenous-retinal-detachment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165024.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">77</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">70</span> Medical Diagnosis of Retinal Diseases Using Artificial Intelligence Deep Learning Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ethan%20James">Ethan James</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=imaging" title=" imaging"> imaging</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20devices" title=" medical devices"> medical devices</a>, <a href="https://publications.waset.org/abstracts/search?q=ophthalmic%20devices" title=" ophthalmic devices"> ophthalmic devices</a>, <a href="https://publications.waset.org/abstracts/search?q=ophthalmology" title=" ophthalmology"> ophthalmology</a>, <a href="https://publications.waset.org/abstracts/search?q=retina" title=" retina"> retina</a> </p> <a href="https://publications.waset.org/abstracts/127742/medical-diagnosis-of-retinal-diseases-using-artificial-intelligence-deep-learning-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/127742.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">181</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">69</span> An Unusual Occurrence: Typhoid Retinitis with Kyrieleis' Vasculitis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aditya%20Sethi">Aditya Sethi</a>, <a href="https://publications.waset.org/abstracts/search?q=Vaibhav%20Sethi"> Vaibhav Sethi</a>, <a href="https://publications.waset.org/abstracts/search?q=Shenouda%20Girgis"> Shenouda Girgis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We present a case of a 31-year-old female who presented with a three week history of left eye blurry vision following a fever. She was diagnosed with Typhoid fever, confirmed by a positive Widal test report. On examination, her best corrected visual acuity in the right eye was 20/20 and in the left eye was 20/60. Fundus examination of the right eye showed a focal area of retinitis with retinal haemorrhages along the superior arcade within the macula. There was also focal area of retinitis with superficial retinal haemorrhages along the superior arcade vessels. There was also presence of multiple yellowish white exudates within the adjacent retinal artery arranged in a beaded pattern, suggestive of Kyrieleis' vasculitis. Optical Coherence Tomography (OCT) of the left eye demonstrated cystoid macula edema with serous foveal detachment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=typhoid%20retinitis" title="typhoid retinitis">typhoid retinitis</a>, <a href="https://publications.waset.org/abstracts/search?q=Kyrieleis%E2%80%99%20vasculitis" title=" Kyrieleis’ vasculitis"> Kyrieleis’ vasculitis</a>, <a href="https://publications.waset.org/abstracts/search?q=immune-mediated%20retinitis" title=" immune-mediated retinitis"> immune-mediated retinitis</a>, <a href="https://publications.waset.org/abstracts/search?q=post-fever%20retinitis" title=" post-fever retinitis"> post-fever retinitis</a>, <a href="https://publications.waset.org/abstracts/search?q=typhoid%20retinopathy" title=" typhoid retinopathy"> typhoid retinopathy</a>, <a href="https://publications.waset.org/abstracts/search?q=retinitis" title=" retinitis"> retinitis</a> </p> <a href="https://publications.waset.org/abstracts/132860/an-unusual-occurrence-typhoid-retinitis-with-kyrieleis-vasculitis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132860.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">178</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">68</span> External Retinal Prosthesis Image Processing System Used One-Cue Saliency Map Based on DSP</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yili%20Chen">Yili Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Jixiang%20Fu"> Jixiang Fu</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhihua%20Liu"> Zhihua Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhicheng%20Zhang"> Zhicheng Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Rongmao%20Li"> Rongmao Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Nan%20Fu"> Nan Fu</a>, <a href="https://publications.waset.org/abstracts/search?q=Yaoqin%20Xie"> Yaoqin Xie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Retinal prothesis is designed to help the blind to get some sight.It is made up of internal part and external part.In external part ,there is made up of camera, image processing, and RF transmitter.In internal part, there is RF receiver, implant chip,micro-electrode.The image got from the camera should be processed by suitable stragies to corresponds to stimulus the electrode.Nowadays, the number of the micro-electrode is hundreds and we don’t know the mechanism how the elctrode stimulus the optic nerve, an easy way to the hypothesis is that the pixel in the image is correspondence to the electrode.So it is a question how to get the important information of the image captured from the picture.There are many strategies to experimented to get the most important information as soon as possible, due to the real time system.ROI is a useful algorithem to extract the region of the interest.Our paper will explain the details of the orinciples and functions of the ROI.And based on this, we simplified the ROI algrithem,and used it in outside image prcessing DSP system of the retinal prothesis.Results show that our image processing stratiges is suitable for real-time retinal prothesis and can cut redundant information and help useful information to express in the low-size image. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title="image processing">image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=region%20of%20interest" title=" region of interest"> region of interest</a>, <a href="https://publications.waset.org/abstracts/search?q=saliency%20map" title=" saliency map"> saliency map</a>, <a href="https://publications.waset.org/abstracts/search?q=low-size%20image" title=" low-size image"> low-size image</a>, <a href="https://publications.waset.org/abstracts/search?q=useful%20information%20express" title=" useful information express"> useful information express</a>, <a href="https://publications.waset.org/abstracts/search?q=cut%20redundant%20information%20in%20image" title=" cut redundant information in image"> cut redundant information in image</a> </p> <a href="https://publications.waset.org/abstracts/37364/external-retinal-prosthesis-image-processing-system-used-one-cue-saliency-map-based-on-dsp" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37364.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">282</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">67</span> Characterization of Retinal Pigmented Cell Epithelium Cell Sheet Cultivated on Synthetic Scaffold</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tan%20Yong%20Sheng%20Edgar">Tan Yong Sheng Edgar</a>, <a href="https://publications.waset.org/abstracts/search?q=Yeong%20Wai%20Yee"> Yeong Wai Yee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Age-related macular degeneration (AMD) is one of the leading cause of blindness. It can cause severe visual loss due to damaged retinal pigment epithelium (RPE). RPE is an important component of the retinal tissue. It functions as a transducing boundary for visual perception making it an essential factor for sight. The RPE also functions as a metabolically complex and functional cell layer that is responsible for the local homeostasis and maintenance of the extra photoreceptor environment. Thus one of the suggested method of treating such diseases would be regenerating these RPE cells. As such, we intend to grow these cells using a synthetic scaffold to provide a stable environment that reduces the batch effects found in natural scaffolds. Stiffness of the scaffold will also be investigated to determine the optimal Young’s modulus for cultivating these cells. The cells will be generated into a monolayer cell sheet and their functions such as formation of tight junctions and gene expression patterns will be assessed to evaluate the cell sheet quality compared to a native RPE tissue. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=RPE" title="RPE">RPE</a>, <a href="https://publications.waset.org/abstracts/search?q=scaffold" title=" scaffold"> scaffold</a>, <a href="https://publications.waset.org/abstracts/search?q=characterization" title=" characterization"> characterization</a>, <a href="https://publications.waset.org/abstracts/search?q=biomaterials" title=" biomaterials"> biomaterials</a>, <a href="https://publications.waset.org/abstracts/search?q=colloids%20and%20nanomedicine" title=" colloids and nanomedicine"> colloids and nanomedicine</a> </p> <a href="https://publications.waset.org/abstracts/13922/characterization-of-retinal-pigmented-cell-epithelium-cell-sheet-cultivated-on-synthetic-scaffold" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13922.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">436</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">66</span> Automatic Method for Exudates and Hemorrhages Detection from Fundus Retinal Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Biran">A. Biran</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Sobhe%20Bidari"> P. Sobhe Bidari</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Raahemifar"> K. Raahemifar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=diabetic%20retinopathy" title="diabetic retinopathy">diabetic retinopathy</a>, <a href="https://publications.waset.org/abstracts/search?q=fundus" title=" fundus"> fundus</a>, <a href="https://publications.waset.org/abstracts/search?q=CHT" title=" CHT"> CHT</a>, <a href="https://publications.waset.org/abstracts/search?q=exudates" title=" exudates"> exudates</a>, <a href="https://publications.waset.org/abstracts/search?q=hemorrhages" title=" hemorrhages"> hemorrhages</a> </p> <a href="https://publications.waset.org/abstracts/52591/automatic-method-for-exudates-and-hemorrhages-detection-from-fundus-retinal-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52591.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">272</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">65</span> Segmenting 3D Optical Coherence Tomography Images Using a Kalman Filter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Deniz%20Guven">Deniz Guven</a>, <a href="https://publications.waset.org/abstracts/search?q=Wil%20Ward"> Wil Ward</a>, <a href="https://publications.waset.org/abstracts/search?q=Jinming%20Duan"> Jinming Duan</a>, <a href="https://publications.waset.org/abstracts/search?q=Li%20Bai"> Li Bai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Over the past two decades or so, Optical Coherence Tomography (OCT) has been used to diagnose retina and optic nerve diseases. The retinal nerve fibre layer, for example, is a powerful diagnostic marker for detecting and staging glaucoma. With the advances in optical imaging hardware, the adoption of OCT is now commonplace in clinics. More and more OCT images are being generated, and for these OCT images to have clinical applicability, accurate automated OCT image segmentation software is needed. Oct image segmentation is still an active research area, as OCT images are inherently noisy, with the multiplicative speckling noise. Simple edge detection algorithms are unsuitable for detecting retinal layer boundaries in OCT images. Intensity fluctuation, motion artefact, and the presence of blood vessels also decrease further OCT image quality. In this paper, we introduce a new method for segmenting three-dimensional (3D) OCT images. This involves the use of a Kalman filter, which is commonly used in computer vision for object tracking. The Kalman filter is applied to the 3D OCT image volume to track the retinal layer boundaries through the slices within the volume and thus segmenting the 3D image. Specifically, after some pre-processing of the OCT images, points on the retinal layer boundaries in the first image are identified, and curve fitting is applied to them such that the layer boundaries can be represented by the coefficients of the curve equations. These coefficients then form the state space for the Kalman Filter. The filter then produces an optimal estimate of the current state of the system by updating its previous state using the measurements available in the form of a feedback control loop. The results show that the algorithm can be used to segment the retinal layers in OCT images. One of the limitations of the current algorithm is that the curve representation of the retinal layer boundary does not work well when the layer boundary is split into two, e.g., at the optic nerve, the layer boundary split into two. This maybe resolved by using a different approach to representing the boundaries, such as b-splines or level sets. The use of a Kalman filter shows promise to developing accurate and effective 3D OCT segmentation methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optical%20coherence%20tomography" title="optical coherence tomography">optical coherence tomography</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20segmentation" title=" image segmentation"> image segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=object%20tracking" title=" object tracking"> object tracking</a> </p> <a href="https://publications.waset.org/abstracts/66524/segmenting-3d-optical-coherence-tomography-images-using-a-kalman-filter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66524.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">482</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">64</span> Computer-Aided Exudate Diagnosis for the Screening of Diabetic Retinopathy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shu-Min%20Tsao">Shu-Min Tsao</a>, <a href="https://publications.waset.org/abstracts/search?q=Chung-Ming%20Lo"> Chung-Ming Lo</a>, <a href="https://publications.waset.org/abstracts/search?q=Shao-Chun%20Chen"> Shao-Chun Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Most diabetes patients tend to suffer from its complication of retina diseases. Therefore, early detection and early treatment are important. In clinical examinations, using color fundus image was the most convenient and available examination method. According to the exudates appeared in the retinal image, the status of retina can be confirmed. However, the routine screening of diabetic retinopathy by color fundus images would bring time-consuming tasks to physicians. This study thus proposed a computer-aided exudate diagnosis for the screening of diabetic retinopathy. After removing vessels and optic disc in the retinal image, six quantitative features including region number, region area, and gray-scale values etc… were extracted from the remaining regions for classification. As results, all six features were evaluated to be statistically significant (p-value < 0.001). The accuracy of classifying the retinal images into normal and diabetic retinopathy achieved 82%. Based on this system, the clinical workload could be reduced. The examination procedure may also be improved to be more efficient. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computer-aided%20diagnosis" title="computer-aided diagnosis">computer-aided diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=diabetic%20retinopathy" title=" diabetic retinopathy"> diabetic retinopathy</a>, <a href="https://publications.waset.org/abstracts/search?q=exudate" title=" exudate"> exudate</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a> </p> <a href="https://publications.waset.org/abstracts/70086/computer-aided-exudate-diagnosis-for-the-screening-of-diabetic-retinopathy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70086.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">270</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">63</span> Central Retinal Venous Occlusion Associated O Bilateral Optic Nerve Infiltration Revealing Relapse Of An Acute Lymphoblastic Leukemia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fendouli%20Ines">Fendouli Ines</a>, <a href="https://publications.waset.org/abstracts/search?q=Zaafrane%20Nesrine"> Zaafrane Nesrine</a>, <a href="https://publications.waset.org/abstracts/search?q=Mhamdi%20Hana"> Mhamdi Hana</a>, <a href="https://publications.waset.org/abstracts/search?q=Knani%20Leila"> Knani Leila</a>, <a href="https://publications.waset.org/abstracts/search?q=Ghorbel%20Mohamed"> Ghorbel Mohamed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Ocular infiltration of leukemia can involve orbit, uveal tract, retina and optic nerve. It may result from direct ocular infiltration by leukemic cells or indirect ocular involvement resulting from secondary hematologic changes, opportunistic infections and complications of various modalities of therapy. We here in report a case of central venous retinal occlusion associated to optic nerve infiltration as presenting signs of a relapse of acute lymphoblastic leukemia. Case Report: A twelve-year-old male -patient of acute B lymphoblastic leukemia presented with headaches and bilateral blurred vision in the left ee. Ophthalmic examination showed a visual acuity reduced to counting fingers in the right eye and no light perception in the left eye. Funduscopy revealed a voluminous disc edema surrounded by retinal haemorrhages in the right eye, and venous tortusities, papillary edema, and hemorrages suggesting central retinal venous occlusion in the LE. Swept source optical coherence tomography revealed a serous retinal detachment in the RE and .hyperreflective inner layers with macular edema in the left eye. Cerebro-orbital MRI showed bilateral thickened left optic nerve. There were no radiological signs of true papillary edema due to intracranial hypertension secondary to central nervous system involvement. Myelogram and lumbar punction demonstrated blast infiltration and confirmed ocular relapse of the leukemia. Conclusion: Ocular involvement lymphoblastic acute leukemias decreased since the introduction of a systematic prophylactic treatment of central nervous system. Periodic ophthalmic examination is necessary to allow early diagnosis and treatment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=acute%20leukemia" title="acute leukemia">acute leukemia</a>, <a href="https://publications.waset.org/abstracts/search?q=optic%20nerve" title=" optic nerve"> optic nerve</a>, <a href="https://publications.waset.org/abstracts/search?q=infiltration" title=" infiltration"> infiltration</a>, <a href="https://publications.waset.org/abstracts/search?q=relapse" title=" relapse"> relapse</a> </p> <a href="https://publications.waset.org/abstracts/167221/central-retinal-venous-occlusion-associated-o-bilateral-optic-nerve-infiltration-revealing-relapse-of-an-acute-lymphoblastic-leukemia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/167221.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">90</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">62</span> Support Vector Machine Based Retinal Therapeutic for Glaucoma Using Machine Learning Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20S.%20Jagadeesh%20Kumar">P. S. Jagadeesh Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Mingmin%20Pan"> Mingmin Pan</a>, <a href="https://publications.waset.org/abstracts/search?q=Yang%20Yung"> Yang Yung</a>, <a href="https://publications.waset.org/abstracts/search?q=Tracy%20Lin%20Huan"> Tracy Lin Huan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Glaucoma is a group of visual maladies represented by the scheduled optic nerve neuropathy; means to the increasing dwindling in vision ground, resulting in loss of sight. In this paper, a novel support vector machine based retinal therapeutic for glaucoma using machine learning algorithm is conservative. The algorithm has fitting pragmatism; subsequently sustained on correlation clustering mode, it visualizes perfect computations in the multi-dimensional space. Support vector clustering turns out to be comparable to the scale-space advance that investigates the cluster organization by means of a kernel density estimation of the likelihood distribution, where cluster midpoints are idiosyncratic by the neighborhood maxima of the concreteness. The predicted planning has 91% attainment rate on data set deterrent on a consolidation of 500 realistic images of resolute and glaucoma retina; therefore, the computational benefit of depending on the cluster overlapping system pedestal on machine learning algorithm has complete performance in glaucoma therapeutic. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20learning%20algorithm" title="machine learning algorithm">machine learning algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=correlation%20clustering%20mode" title=" correlation clustering mode"> correlation clustering mode</a>, <a href="https://publications.waset.org/abstracts/search?q=cluster%20overlapping%20system" title=" cluster overlapping system"> cluster overlapping system</a>, <a href="https://publications.waset.org/abstracts/search?q=glaucoma" title=" glaucoma"> glaucoma</a>, <a href="https://publications.waset.org/abstracts/search?q=kernel%20density%20estimation" title=" kernel density estimation"> kernel density estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=retinal%20therapeutic" title=" retinal therapeutic"> retinal therapeutic</a> </p> <a href="https://publications.waset.org/abstracts/80153/support-vector-machine-based-retinal-therapeutic-for-glaucoma-using-machine-learning-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80153.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">254</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" 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