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images</title> <meta name="description" content="Search results for: body images"> <meta name="keywords" content="body images"> <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 navbar-toggler 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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="body images"> <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> 6233</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: body images</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6233</span> Body Mass Hurts Adolescent Girls More than Thin-Ideal Images </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Javaid%20Marium">Javaid Marium</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20Iftikhar"> Ahmad Iftikhar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study was aimed to identify factors that affect negative mood and body image dissatisfaction in women. positive and negative affect, self esteem, body image satisfaction and figure rating scale was administered to 97 female undergraduate students. This served as a base line data for correlation analysis in the first instance. One week later participants who volunteered to appear in the second phase of the study (N=47) were shown thin- ideal images as an intervention and soon after they completed positive and negative affect schedule and body image states scale again as a post test. Results indicated body mass as a strong negative predictor of body image dis/satisfaction, self esteem was a moderate predictor and mood was not a significant predictor. The participants whose actual body shape was markedly discrepant with the ideally desired body shape had significantly low level of body image satisfaction (p < .001) than those with low discrepancy. Similar results were found for self esteem (p < .004). Both self esteem and body mass predicted body satisfaction about equally and significantly. However, on viewing thin-ideal images, the participants of different body weight showed no change in their body image satisfaction than before. Only the overweight participants were significantly affected on negative mood as a short term reaction after viewing the thin ideal images. Comparing the three groups based on their body mass, one-way ANOVA revealed significant difference on negative mood as well as body image satisfaction. This reveals body mass as a potent and stable factor that consistently and strongly affected body satisfaction not the transient portrayal of thin ideal images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=body%20image%20satisfaction" title="body image satisfaction">body image satisfaction</a>, <a href="https://publications.waset.org/abstracts/search?q=thin-ideal%20images" title=" thin-ideal images"> thin-ideal images</a>, <a href="https://publications.waset.org/abstracts/search?q=media" title=" media"> media</a>, <a href="https://publications.waset.org/abstracts/search?q=mood%20affects" title=" mood affects"> mood affects</a>, <a href="https://publications.waset.org/abstracts/search?q=self%20esteem" title=" self esteem "> self esteem </a> </p> <a href="https://publications.waset.org/abstracts/26924/body-mass-hurts-adolescent-girls-more-than-thin-ideal-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26924.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">284</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">6232</span> Constructing Masculinity through Images: Content Analysis of Lifestyle Magazines in Croatia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Marija%20Lon%C4%8Dar">Marija Lon膷ar</a>, <a href="https://publications.waset.org/abstracts/search?q=Zorana%20%C5%A0uljug%20Vu%C4%8Dica"> Zorana 艩uljug Vu膷ica</a>, <a href="https://publications.waset.org/abstracts/search?q=Magdalena%20Nigoevi%C4%87"> Magdalena Nigoevi膰</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Diverse social, cultural and economic trends and changes in contemporary societies influence the ways masculinity is represented in a variety of media. Masculinity is constructed within media images as a dynamic process that changes slowly over time and is shaped by various social factors. In many societies, dominant masculinity is still associated with authority, heterosexuality, marriage, professional and financial success, ethnic dominance and physical strength. But contemporary media depict men in ways that suggest a change in the approach to media images. The number of media images of men, which promote men’s identity through their body, have increased. With the male body more scrutinized and commodified, it is necessary to highlight how the body is represented and which visual elements are crucial since the body has an important role in the construction of masculinities. The study includes content analysis of male body images in the advertisements of different men’s and women’s lifestyle magazines available in Croatia. The main aim was to explore how masculinities are currently being portrayed through body regarding age, physical appearance, fashion, touch and gaze. The findings are also discussed in relation to female images since women are central in many of the processes constructing masculinities and according to the recent conceptualization of masculinity. Although the construction of male images varies through body features, almost all of them convey the message that men’s identity could be managed through manipulation and by enhancing the appearance. Furthermore, they suggest that men should engage in “bodywork” through advertised products, activities and/or practices, in order to achieve their preferred social image. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=body%20images" title="body images">body images</a>, <a href="https://publications.waset.org/abstracts/search?q=content%20analysis" title=" content analysis"> content analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=lifestyle%20magazines" title=" lifestyle magazines"> lifestyle magazines</a>, <a href="https://publications.waset.org/abstracts/search?q=masculinity" title=" masculinity"> masculinity</a> </p> <a href="https://publications.waset.org/abstracts/56871/constructing-masculinity-through-images-content-analysis-of-lifestyle-magazines-in-croatia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56871.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">245</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">6231</span> Prediction of Bodyweight of Cattle by Artificial Neural Networks Using Digital Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yal%C3%A7%C4%B1n%20Bozkurt">Yal莽谋n Bozkurt</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Prediction models were developed for accurate prediction of bodyweight (BW) by using Digital Images of beef cattle body dimensions by Artificial Neural Networks (ANN). For this purpose, the animal data were collected at a private slaughter house and the digital images and the weights of each live animal were taken just before they were slaughtered and the body dimensions such as digital wither height (DJWH), digital body length (DJBL), digital body depth (DJBD), digital hip width (DJHW), digital hip height (DJHH) and digital pin bone length (DJPL) were determined from the images, using the data with 1069 observations for each traits. Then, prediction models were developed by ANN. Digital body measurements were analysed by ANN for body prediction and R2 values of DJBL, DJWH, DJHW, DJBD, DJHH and DJPL were approximately 94.32, 91.31, 80.70, 83.61, 89.45 and 70.56 % respectively. It can be concluded that in management situations where BW cannot be measured it can be predicted accurately by measuring DJBL and DJWH alone or both DJBD and even DJHH and different models may be needed to predict BW in different feeding and environmental conditions and breeds <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title="artificial neural networks">artificial neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=bodyweight" title=" bodyweight"> bodyweight</a>, <a href="https://publications.waset.org/abstracts/search?q=cattle" title=" cattle"> cattle</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20body%20measurements" title=" digital body measurements"> digital body measurements</a> </p> <a href="https://publications.waset.org/abstracts/71446/prediction-of-bodyweight-of-cattle-by-artificial-neural-networks-using-digital-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71446.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">372</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">6230</span> Using Machine Learning to Classify Different Body Parts and Determine Healthiness</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zachary%20Pan">Zachary Pan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=body%20part" title="body part">body part</a>, <a href="https://publications.waset.org/abstracts/search?q=healthcare" title=" healthcare"> healthcare</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20networks" title=" neural networks"> neural networks</a> </p> <a href="https://publications.waset.org/abstracts/160577/using-machine-learning-to-classify-different-body-parts-and-determine-healthiness" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160577.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">103</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">6229</span> Water Body Detection and Estimation from Landsat Satellite Images Using Deep Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Devaki">M. Devaki</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20B.%20Jayanthi"> K. B. Jayanthi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=water%20body" title="water body">water body</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=satellite%20images" title=" satellite images"> satellite images</a>, <a href="https://publications.waset.org/abstracts/search?q=convolution%20neural%20network" title=" convolution neural network"> convolution neural network</a> </p> <a href="https://publications.waset.org/abstracts/162827/water-body-detection-and-estimation-from-landsat-satellite-images-using-deep-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162827.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">89</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">6228</span> A Study of Parameters That Have an Influence on Fabric Prints in Judging the Attractiveness of a Female Body Shape</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Man%20N.%20M.%20Cheung">Man N. M. Cheung</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In judging the attractiveness of female body shape, visual sense is one of the important means. The ratio and proportion of body shape influence the perception of female physical attractiveness. This study aims to examine visual perception of digital textile prints on a virtual 3D model in judging the attractiveness of the body shape. Also, investigate the influences when using different shape parameters and their relationships. Participants were asked to conduct a set of questionnaires with images to rank the attractiveness of the female body shape. Results showed that morphing the fabric prints with a certain ratio and combination of shape parameters - waist and hip, can enhance the attractiveness of the female body shape. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=digital%20printing" title="digital printing">digital printing</a>, <a href="https://publications.waset.org/abstracts/search?q=3D%20body%20modeling" title=" 3D body modeling"> 3D body modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=fashion%20print%20design" title=" fashion print design"> fashion print design</a>, <a href="https://publications.waset.org/abstracts/search?q=body%20shape%20attractiveness" title=" body shape attractiveness"> body shape attractiveness</a> </p> <a href="https://publications.waset.org/abstracts/96035/a-study-of-parameters-that-have-an-influence-on-fabric-prints-in-judging-the-attractiveness-of-a-female-body-shape" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/96035.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">6227</span> A New Approach to Image Stitching of Radiographic Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Somaya%20Adwan">Somaya Adwan</a>, <a href="https://publications.waset.org/abstracts/search?q=Rasha%20Majed"> Rasha Majed</a>, <a href="https://publications.waset.org/abstracts/search?q=Lamya%27a%20Majed"> Lamya'a Majed</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamzah%20Arof"> Hamzah Arof</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to produce images with whole body parts, X-ray of different portions of the body parts is assembled using image stitching methods. A new method for image stitching that exploits mutually feature based method and direct based method to identify and merge pairs of X-ray medical images is presented in this paper. The performance of the proposed method based on this hybrid approach is investigated in this paper. The ability of the proposed method to stitch and merge the overlapping pairs of images is demonstrated. Our proposed method display comparable if not superior performance to other feature based methods that are mentioned in the literature on the standard databases. These results are promising and demonstrate the potential of the proposed method for further development to tackle more advanced stitching problems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20stitching" title="image stitching">image stitching</a>, <a href="https://publications.waset.org/abstracts/search?q=direct%20based%20method" title=" direct based method"> direct based method</a>, <a href="https://publications.waset.org/abstracts/search?q=panoramic%20image" title=" panoramic image"> panoramic image</a>, <a href="https://publications.waset.org/abstracts/search?q=X-ray" title=" X-ray"> X-ray</a> </p> <a href="https://publications.waset.org/abstracts/17610/a-new-approach-to-image-stitching-of-radiographic-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17610.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">541</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">6226</span> Communication About Health and Fitness in Media and Its Hidden Message About Objectification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emiko%20Suzuki">Emiko Suzuki</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Although fitness is defined as the body鈥檚 ability to respond to the demand of physical activity without undue fatigue in health science, in media oftentimes physical activity is presented as means to an attractive body rather than a fit and healthy one. Of all types of media, Instagram is becoming an increasingly persuasive source of information and advice on health and fitness, where individuals conceptualize what health and fitness mean for them. However, this user-generated and unregulated platform can be problematic, as it can communicate misleading information about health and fitness and possibly leading individuals to psychological problems such as eating disorders. In fact, previous research has shown that some messages that were posted with a tag that related to inspire others to do fitness, in fact, encouraged distancing the self from the internal needs of the body. For this reason, this present study aims to explore how health and fitness are communicated on Instagram by analyzing images and texts. A content analysis of images that were labeled with particular hashtags was performed, followed by a thematic analysis of texts from the same set of images. The result shows an interesting insight about messages about how health and fitness are communicated from companies through media, then digested and further shared among communities on Instagram. The study explores how the use of visual focused way of communicating health and fitness can lead to the dehumanization of human bodies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Instagram" title="Instagram">Instagram</a>, <a href="https://publications.waset.org/abstracts/search?q=fitness" title=" fitness"> fitness</a>, <a href="https://publications.waset.org/abstracts/search?q=dehumanization" title=" dehumanization"> dehumanization</a>, <a href="https://publications.waset.org/abstracts/search?q=body%20image" title=" body image"> body image</a>, <a href="https://publications.waset.org/abstracts/search?q=embodiment" title=" embodiment"> embodiment</a> </p> <a href="https://publications.waset.org/abstracts/138163/communication-about-health-and-fitness-in-media-and-its-hidden-message-about-objectification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/138163.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">138</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">6225</span> Preliminary Evaluation of Maximum Intensity Projection SPECT Imaging for Whole Body Tc-99m Hydroxymethylene Diphosphonate Bone Scanning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yasuyuki%20Takahashi">Yasuyuki Takahashi</a>, <a href="https://publications.waset.org/abstracts/search?q=Hirotaka%20Shimada"> Hirotaka Shimada</a>, <a href="https://publications.waset.org/abstracts/search?q=Kyoko%20Saito"> Kyoko Saito</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Bone scintigraphy is widely used as a screening tool for bone metastases. However, the 180 to 240 minutes (min) waiting time after the intravenous (i.v.) injection of the tracer is both long and tiresome. To solve this shortcoming, a bone scan with a shorter waiting time is needed. In this study, we applied the Maximum Intensity Projection (MIP) and triple energy window (TEW) scatter correction to a whole body bone SPECT (Merged SPECT) and investigated shortening the waiting time. Methods: In a preliminary phantom study, hot gels of 99mTc-HMDP were inserted into sets of rods with diameters ranging from 4 to 19 mm. Each rod set covered a sector of a cylindrical phantom. The activity concentration of all rods was 2.5 times that of the background in the cylindrical body of the phantom. In the human study, SPECT images were obtained from chest to abdomen at 30 to 180 min after 99mTc- hydroxymethylene diphosphonate (HMDP) injection of healthy volunteers. For both studies, MIP images were reconstructed. Planar whole body images of the patients were also obtained. These were acquired at 200 min. The image quality of the SPECT and the planar images was compared. Additionally, 36 patients with breast cancer were scanned in the same way. The delectability of uptake regions (metastases) was compared visually. Results: In the phantom study, a 4 mm size hot gel was difficult to depict on the conventional SPECT, but MIP images could recognize it clearly. For both the healthy volunteers and the clinical patients, the accumulation of 99mTc-HMDP in the SPECT was good as early as 90 min. All findings of both image sets were in agreement. Conclusion: In phantoms, images from MIP with TEW scatter correction could detect all rods down to those with a diameter of 4 mm. In patients, MIP reconstruction with TEW scatter correction could improve the detectability of hot lesions. In addition, the time between injection and imaging could be shortened from that conventionally used for whole body scans. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=merged%20SPECT" title="merged SPECT">merged SPECT</a>, <a href="https://publications.waset.org/abstracts/search?q=MIP" title=" MIP"> MIP</a>, <a href="https://publications.waset.org/abstracts/search?q=TEW%20scatter%20correction" title=" TEW scatter correction"> TEW scatter correction</a>, <a href="https://publications.waset.org/abstracts/search?q=99mTc-HMDP" title=" 99mTc-HMDP"> 99mTc-HMDP</a> </p> <a href="https://publications.waset.org/abstracts/13577/preliminary-evaluation-of-maximum-intensity-projection-spect-imaging-for-whole-body-tc-99m-hydroxymethylene-diphosphonate-bone-scanning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13577.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">412</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">6224</span> An Examination of the Relationship between Adolescents' Social Media Use and Social Appearance Anxiety</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aynur%20B%C3%BCt%C3%BCn%20Ayhan">Aynur B眉t眉n Ayhan</a>, <a href="https://publications.waset.org/abstracts/search?q=Utku%20Beyaz%C4%B1t"> Utku Beyaz谋t</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Adolescents can be heavily influenced by social media content as they develop their identities and body images. Therefore, the intensive use of social media platforms may have important effects on their body image beliefs. In this context, the objective of the present study was to assess the relationship between adolescents' social media use and their body image concerns. The study included 265 adolescents (133 girls and 132 boys) between the ages of 15 and 17 who were attending a high school in Ankara, T眉rkiye. In the study, the adolescents were administered the Social Media Addiction Scale to assess their level of social media use and the Social Appearance Anxiety Scale to assess their social appearance anxiety. Prior to analysis, a normality test was applied, and it was determined that the data displayed a non-parametric distribution. As a result, a significant positive relationship (r=.322, p<.01) was found between adolescents' level of social use and social appearance anxiety. It was also determined that social media addiction and social appearance anxiety significantly differed (p<.05) according to adolescents' opinions about their own bodies, being influenced by body images they see on social media and weight perceptions. The findings suggest that social media use should be managed carefully for adolescents to develop a healthy body image. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=social%20media" title="social media">social media</a>, <a href="https://publications.waset.org/abstracts/search?q=adolescent" title=" adolescent"> adolescent</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20appearence" title=" social appearence"> social appearence</a>, <a href="https://publications.waset.org/abstracts/search?q=anxiety" title=" anxiety"> anxiety</a> </p> <a href="https://publications.waset.org/abstracts/193004/an-examination-of-the-relationship-between-adolescents-social-media-use-and-social-appearance-anxiety" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/193004.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">23</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">6223</span> Research Approaches for Identifying Images of the Past in the Built Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20Al-Zoabi">Ahmad Al-Zoabi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Development of research approaches for identifying images of the past in the built environment is at a beginning stage, and a review of the current literature reveals a limited body of research in this area. This study seeks to make a contribution to fill this void. It investigates the theoretical and empirical studies that examine the built environment as a medium for communicating the past in order to understand how images of the past are operationalized in these studies. Findings revealed that image could be operationalized in several ways depending on the focus of the study. Three concerns were addressed in this study when defining the image of the past: (a) to investigate an 'everyday' popular image of the past; (b) to look at the building's image as an integrated part of a larger image for the city; and (c) to find patterns within residents' images of the past. This study concludes that a future study is needed to address the effects of different scales (size and depth of history) of cities and of different cultural backgrounds of images of the past. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=architecture" title="architecture">architecture</a>, <a href="https://publications.waset.org/abstracts/search?q=built%20environment" title=" built environment"> built environment</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20of%20the%20past" title=" image of the past"> image of the past</a>, <a href="https://publications.waset.org/abstracts/search?q=research%20approaches" title=" research approaches"> research approaches</a> </p> <a href="https://publications.waset.org/abstracts/66594/research-approaches-for-identifying-images-of-the-past-in-the-built-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66594.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">316</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">6222</span> Wireless Capsule Endoscope - Antenna and Channel Characterization </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mona%20Elhelbawy">Mona Elhelbawy</a>, <a href="https://publications.waset.org/abstracts/search?q=Mac%20Gray"> Mac Gray</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traditional wired endoscopy is an intrusive process that requires a long flexible tube to be inserted through the patient鈥檚 mouth while intravenously sedated. Only images of the upper 4 feet of stomach, colon, and rectum can be captured, leaving the remaining 20 feet of small intestines. Wireless capsule endoscopy offers a painless, non-intrusive, efficient and effective alternative to traditional endoscopy. In wireless capsule endoscopy (WCE), ingestible vitamin-pill-shaped capsules with imaging capabilities, sensors, batteries, and antennas are designed to send images of the gastrointestinal (GI) tract in real time. In this paper, we investigate the radiation performance and specific absorption rate (SAR) of a miniature conformal capsule antenna operating at the Medical Implant Communication Service (MICS) frequency band in the human body. We perform numerical simulations using the finite element method based commercial software, high-frequency structure simulator (HFSS) and the ANSYS human body model (HBM). We also investigate the in-body channel characteristics between the implantable capsule and an external antenna placed on the surface of the human body. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=IEEE%20802.15.6" title="IEEE 802.15.6">IEEE 802.15.6</a>, <a href="https://publications.waset.org/abstracts/search?q=MICS" title=" MICS"> MICS</a>, <a href="https://publications.waset.org/abstracts/search?q=SAR" title=" SAR"> SAR</a>, <a href="https://publications.waset.org/abstracts/search?q=WCE" title=" WCE"> WCE</a> </p> <a href="https://publications.waset.org/abstracts/129035/wireless-capsule-endoscope-antenna-and-channel-characterization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/129035.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">127</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">6221</span> Rhetoric and Renarrative Structure of Digital Images in Trans-Media</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yang%20Geng">Yang Geng</a>, <a href="https://publications.waset.org/abstracts/search?q=Anqi%20Zhao"> Anqi Zhao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The misreading theory of Harold Bloom provides a new diachronic perspective as an approach to the consistency between rhetoric of digital technology, dynamic movement of digital images and uncertain meaning of text. Reinterpreting the diachroneity of 'intertextuality' in the context of misreading theory extended the range of the 'intermediality' of transmedia to the intense tension between digital images and symbolic images throughout history of images. With the analogy between six categories of revisionary ratios and six steps of digital transformation, digital rhetoric might be illustrated as a linear process reflecting dynamic, intensive relations between digital moving images and original static images. Finally, it was concluded that two-way framework of the rhetoric of transformation of digital images and reversed served as a renarrative structure to revive static images by reconnecting them with digital moving images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=rhetoric" title="rhetoric">rhetoric</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20art" title=" digital art"> digital art</a>, <a href="https://publications.waset.org/abstracts/search?q=intermediality" title=" intermediality"> intermediality</a>, <a href="https://publications.waset.org/abstracts/search?q=misreading%20theory" title=" misreading theory"> misreading theory</a> </p> <a href="https://publications.waset.org/abstracts/100230/rhetoric-and-renarrative-structure-of-digital-images-in-trans-media" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/100230.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">256</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">6220</span> A Calibration Method for Temperature Distribution Measurement of Thermochromic Liquid Crystal Based on Mathematical Morphology of Hue Image</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Risti%20Suryantari">Risti Suryantari</a>, <a href="https://publications.waset.org/abstracts/search?q=Flaviana"> Flaviana</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this research is to design calibration method of Thermochromic Liquid Crystal for temperature distribution measurement based on mathematical morphology of hue image A glass of water is placed on the surface of sample TLC R25C5W at certain temperature. We use scanner for image acquisition. The true images in RGB format is converted to HSV (hue, saturation, value) by taking of hue without saturation and value. Then the hue images is processed based on mathematical morphology using Matlab2013a software to get better images. There are differences on the final images after processing at each temperature variation based on visualization observation and the statistic value. The value of maximum and mean increase with rising temperature. It could be parameter to identify the temperature of the human body surface like hand or foot surface. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=thermochromic%20liquid%20crystal" title="thermochromic liquid crystal">thermochromic liquid crystal</a>, <a href="https://publications.waset.org/abstracts/search?q=TLC" title=" TLC"> TLC</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical%20morphology" title=" mathematical morphology"> mathematical morphology</a>, <a href="https://publications.waset.org/abstracts/search?q=hue%20image" title=" hue image"> hue image</a> </p> <a href="https://publications.waset.org/abstracts/28961/a-calibration-method-for-temperature-distribution-measurement-of-thermochromic-liquid-crystal-based-on-mathematical-morphology-of-hue-image" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28961.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">472</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">6219</span> A Comparative Study of Medical Image Segmentation Methods for Tumor Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mayssa%20Bensalah">Mayssa Bensalah</a>, <a href="https://publications.waset.org/abstracts/search?q=Atef%20Boujelben"> Atef Boujelben</a>, <a href="https://publications.waset.org/abstracts/search?q=Mouna%20Baklouti"> Mouna Baklouti</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Abid"> Mohamed Abid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Image segmentation has a fundamental role in analysis and interpretation for many applications. The automated segmentation of organs and tissues throughout the body using computed imaging has been rapidly increasing. Indeed, it represents one of the most important parts of clinical diagnostic tools. In this paper, we discuss a thorough literature review of recent methods of tumour segmentation from medical images which are briefly explained with the recent contribution of various researchers. This study was followed by comparing these methods in order to define new directions to develop and improve the performance of the segmentation of the tumour area from medical images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=features%20extraction" title="features extraction">features extraction</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=medical%20images" title=" medical images"> medical images</a>, <a href="https://publications.waset.org/abstracts/search?q=tumor%20detection" title=" tumor detection"> tumor detection</a> </p> <a href="https://publications.waset.org/abstracts/132616/a-comparative-study-of-medical-image-segmentation-methods-for-tumor-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132616.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">167</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">6218</span> Quick Similarity Measurement of Binary Images via Probabilistic Pixel Mapping</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adnan%20A.%20Y.%20Mustafa">Adnan A. Y. Mustafa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper we present a quick technique to measure the similarity between binary images. The technique is based on a probabilistic mapping approach and is fast because only a minute percentage of the image pixels need to be compared to measure the similarity, and not the whole image. We exploit the power of the Probabilistic Matching Model for Binary Images (PMMBI) to arrive at an estimate of the similarity. We show that the estimate is a good approximation of the actual value, and the quality of the estimate can be improved further with increased image mappings. Furthermore, the technique is image size invariant; the similarity between big images can be measured as fast as that for small images. Examples of trials conducted on real images are presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=big%20images" title="big images">big images</a>, <a href="https://publications.waset.org/abstracts/search?q=binary%20images" title=" binary images"> binary images</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20matching" title=" image matching"> image matching</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20similarity" title=" image similarity"> image similarity</a> </p> <a href="https://publications.waset.org/abstracts/89963/quick-similarity-measurement-of-binary-images-via-probabilistic-pixel-mapping" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/89963.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">196</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">6217</span> The Impact of Upward Social Media Comparisons on Body Image and the Role of Physical Appearance Perfectionism and Cognitive Coping</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lauren%20Currell">Lauren Currell</a>, <a href="https://publications.waset.org/abstracts/search?q=Gemma%20Hurst"> Gemma Hurst</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: The present study experimentally investigated the impact of attractive Instagram images on female鈥檚 body image. It also examined whether physical appearance perfectionism and cognitive coping predicted body image following upward comparisons to idealised bodies on Instagram. Methods: One-hundred and fifty-eight females (mean age 24.35 years) were randomly assigned to an experimental (where they compared their bodies to those of Instagram models) or control condition (where they critiqued landscape painting). All participants completed measures on physical appearance perfectionism, cognitive coping, and pre- and post-measures of body image. Results: Comparing one鈥檚 body to idealised bodies on Instagram resulted in increased appearance and weight dissatisfaction and decreased confidence, compared to the control condition. Physical appearance perfectionism and cognitive coping both predicted body image outcomes for the experimental condition. Discussion: Clinical implications, such as the prevention and treatment of body dissatisfaction, are discussed. Strengths and limitations of the current study are also noted, and suggestions for future research are provided. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=perfectionism" title="perfectionism">perfectionism</a>, <a href="https://publications.waset.org/abstracts/search?q=cognitive%20coping" title=" cognitive coping"> cognitive coping</a>, <a href="https://publications.waset.org/abstracts/search?q=body%20image" title=" body image"> body image</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20media" title=" social media"> social media</a> </p> <a href="https://publications.waset.org/abstracts/167086/the-impact-of-upward-social-media-comparisons-on-body-image-and-the-role-of-physical-appearance-perfectionism-and-cognitive-coping" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/167086.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">96</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">6216</span> 3D Guided Image Filtering to Improve Quality of Short-Time Binned Dynamic PET Images Using MRI Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tabassum%20Husain">Tabassum Husain</a>, <a href="https://publications.waset.org/abstracts/search?q=Shen%20Peng%20Li"> Shen Peng Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhaolin%20Chen"> Zhaolin Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper evaluates the usability of 3D Guided Image Filtering to enhance the quality of short-time binned dynamic PET images by using MRI images. Guided image filtering is an edge-preserving filter proposed to enhance 2D images. The 3D filter is applied on 1 and 5-minute binned images. The results are compared with 15-minute binned images and the Gaussian filtering. The guided image filter enhances the quality of dynamic PET images while also preserving important information of the voxels. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dynamic%20PET%20images" title="dynamic PET images">dynamic PET images</a>, <a href="https://publications.waset.org/abstracts/search?q=guided%20image%20filter" title=" guided image filter"> guided image filter</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20enhancement" title=" image enhancement"> image enhancement</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20preservation%20filtering" title=" information preservation filtering"> information preservation filtering</a> </p> <a href="https://publications.waset.org/abstracts/152864/3d-guided-image-filtering-to-improve-quality-of-short-time-binned-dynamic-pet-images-using-mri-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152864.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">132</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">6215</span> Reduction of Speckle Noise in Echocardiographic Images: A Survey</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fathi%20Kallel">Fathi Kallel</a>, <a href="https://publications.waset.org/abstracts/search?q=Saida%20Khachira"> Saida Khachira</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Ben%20Slima"> Mohamed Ben Slima</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Ben%20Hamida"> Ahmed Ben Hamida</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Speckle noise is a main characteristic of cardiac ultrasound images, it corresponding to grainy appearance that degrades the image quality. For this reason, the ultrasound images are difficult to use automatically in clinical use, then treatments are required for this type of images. Then a filtering procedure of these images is necessary to eliminate the speckle noise and to improve the quality of ultrasound images which will be then segmented to extract the necessary forms that exist. In this paper, we present the importance of the pre-treatment step for segmentation. This work is applied to cardiac ultrasound images. In a first step, a comparative study of speckle filtering method will be presented and then we use a segmentation algorithm to locate and extract cardiac structures. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=medical%20image%20processing" title="medical image processing">medical image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=ultrasound%20images" title=" ultrasound images"> ultrasound images</a>, <a href="https://publications.waset.org/abstracts/search?q=Speckle%20noise" title=" Speckle noise"> Speckle noise</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20enhancement" title=" image enhancement"> image enhancement</a>, <a href="https://publications.waset.org/abstracts/search?q=speckle%20filtering" title=" speckle filtering"> speckle filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=segmentation" title=" segmentation"> segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=snakes" title=" snakes"> snakes</a> </p> <a href="https://publications.waset.org/abstracts/19064/reduction-of-speckle-noise-in-echocardiographic-images-a-survey" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19064.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">530</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">6214</span> Subjective Evaluation of Mathematical Morphology Edge Detection on Computed Tomography (CT) Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emhimed%20Saffor">Emhimed Saffor</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the problem of edge detection in digital images is considered. Three methods of edge detection based on mathematical morphology algorithm were applied on two sets (Brain and Chest) CT images. 3x3 filter for first method, 5x5 filter for second method and 7x7 filter for third method under MATLAB programming environment. The results of the above-mentioned methods are subjectively evaluated. The results show these methods are more efficient and satiable for medical images, and they can be used for different other applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CT%20images" title="CT images">CT images</a>, <a href="https://publications.waset.org/abstracts/search?q=Matlab" title=" Matlab"> Matlab</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20images" title=" medical images"> medical images</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/44926/subjective-evaluation-of-mathematical-morphology-edge-detection-on-computed-tomography-ct-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44926.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">338</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">6213</span> Automated Feature Detection and Matching Algorithms for Breast IR Sequence Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chia-Yen%20Lee">Chia-Yen Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Hao-Jen%20Wang"> Hao-Jen Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jhih-Hao%20Lai"> Jhih-Hao Lai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, infrared (IR) imaging has been considered as a potential tool to assess the efficacy of chemotherapy and early detection of breast cancer. Regions of tumor growth with high metabolic rate and angiogenesis phenomenon lead to the high temperatures. Observation of differences between the heat maps in long term is useful to help assess the growth of breast cancer cells and detect breast cancer earlier, wherein the multi-time infrared image alignment technology is a necessary step. Representative feature points detection and matching are essential steps toward the good performance of image registration and quantitative analysis. However, there is no clear boundary on the infrared images and the subject's posture are different for each shot. It cannot adhesive markers on a body surface for a very long period, and it is hard to find anatomic fiducial markers on a body surface. In other words, it鈥檚 difficult to detect and match features in an IR sequence images. In this study, automated feature detection and matching algorithms with two type of automatic feature points (i.e., vascular branch points and modified Harris corner) are developed respectively. The preliminary results show that the proposed method could identify the representative feature points on the IR breast images successfully of 98% accuracy and the matching results of 93% accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Harris%20corner" title="Harris corner">Harris corner</a>, <a href="https://publications.waset.org/abstracts/search?q=infrared%20image" title=" infrared image"> infrared image</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20detection" title=" feature detection"> feature detection</a>, <a href="https://publications.waset.org/abstracts/search?q=registration" title=" registration"> registration</a>, <a href="https://publications.waset.org/abstracts/search?q=matching" title=" matching"> matching</a> </p> <a href="https://publications.waset.org/abstracts/16915/automated-feature-detection-and-matching-algorithms-for-breast-ir-sequence-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16915.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">304</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">6212</span> Automatic Method for Classification of Informative and Noninformative Images in Colonoscopy Video</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nidhal%20K.%20Azawi">Nidhal K. Azawi</a>, <a href="https://publications.waset.org/abstracts/search?q=John%20M.%20Gauch"> John M. Gauch</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=colonoscopy%20classification" title="colonoscopy classification">colonoscopy classification</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20alignment" title=" image alignment"> image alignment</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a> </p> <a href="https://publications.waset.org/abstracts/92461/automatic-method-for-classification-of-informative-and-noninformative-images-in-colonoscopy-video" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/92461.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">253</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">6211</span> Enhancing Learning Ability among Deaf Students by Using Photographic Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aidah%20Alias">Aidah Alias</a>, <a href="https://publications.waset.org/abstracts/search?q=Mustaffa%20Halabi%20Azahari"> Mustaffa Halabi Azahari</a>, <a href="https://publications.waset.org/abstracts/search?q=Adzrool%20Idzwan%20Ismail"> Adzrool Idzwan Ismail</a>, <a href="https://publications.waset.org/abstracts/search?q=Salasiah%20Ahmad"> Salasiah Ahmad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Education is one of the most important elements in a human life. Educations help us in learning and achieve new things in life. The ability of hearing gave us chances to hear voices and it is important in our communication. Hearing stories told by others; hearing news and music to create our creative and sense; seeing and hearing make us understand directly the message trying to deliver. But, what will happen if we are born deaf or having hearing loss while growing up? The objectives of this paper are to identify the current practice in teaching and learning among deaf students and to analyse an appropriate method in enhancing learning process among deaf students. A case study method was employed by using methods of observation and interview to selected deaf students and teachers. The findings indicated that the suitable method of teaching for deaf students is by using pictures and body movement. In other words, by combining these two medium of images and body movement, the best medium that the study suggested is by using video or motion pictures. The study concluded and recommended that video or motion pictures is recommended medium to be used in teaching and learning for deaf students. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deaf" title="deaf">deaf</a>, <a href="https://publications.waset.org/abstracts/search?q=photographic%20images" title=" photographic images"> photographic images</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20communication" title=" visual communication"> visual communication</a>, <a href="https://publications.waset.org/abstracts/search?q=education" title=" education"> education</a>, <a href="https://publications.waset.org/abstracts/search?q=learning%20ability" title=" learning ability"> learning ability</a> </p> <a href="https://publications.waset.org/abstracts/3840/enhancing-learning-ability-among-deaf-students-by-using-photographic-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3840.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">284</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">6210</span> A Convolutional Deep Neural Network Approach for Skin Cancer Detection Using Skin Lesion Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Firas%20Gerges">Firas Gerges</a>, <a href="https://publications.waset.org/abstracts/search?q=Frank%20Y.%20Shih"> Frank Y. Shih</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Malignant melanoma, known simply as melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient's death. When detected early, melanoma is curable. In this paper, we propose a deep learning model (convolutional neural networks) in order to automatically classify skin lesion images as malignant or benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%. <p class="card-text"><strong>Keywords:</strong> <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=skin%20cancer" title=" skin cancer"> skin cancer</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=melanoma" title=" melanoma"> melanoma</a> </p> <a href="https://publications.waset.org/abstracts/134720/a-convolutional-deep-neural-network-approach-for-skin-cancer-detection-using-skin-lesion-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/134720.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">148</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">6209</span> A Way of Converting Color Images to Gray Scale Ones for the Color-Blind: Applying to the part of the Tokyo Subway Map</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Katsuhiro%20Narikiyo">Katsuhiro Narikiyo</a>, <a href="https://publications.waset.org/abstracts/search?q=Shota%20Hashikawa"> Shota Hashikawa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes a way of removing noises and reducing the number of colors contained in a JPEG image. Main purpose of this project is to convert color images to monochrome images for the color-blind. We treat the crispy color images like the Tokyo subway map. Each color in the image has an important information. But for the color blinds, similar colors cannot be distinguished. If we can convert those colors to different gray values, they can distinguish them. Therefore we try to convert color images to monochrome images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=color-blind" title="color-blind">color-blind</a>, <a href="https://publications.waset.org/abstracts/search?q=JPEG" title=" JPEG"> JPEG</a>, <a href="https://publications.waset.org/abstracts/search?q=monochrome%20image" title=" monochrome image"> monochrome image</a>, <a href="https://publications.waset.org/abstracts/search?q=denoise" title=" denoise"> denoise</a> </p> <a href="https://publications.waset.org/abstracts/2968/a-way-of-converting-color-images-to-gray-scale-ones-for-the-color-blind-applying-to-the-part-of-the-tokyo-subway-map" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2968.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">356</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">6208</span> Igbo Art: A Reflection of the Igbo鈥檚 Visual Culture</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=David%20Osa-Egonwa">David Osa-Egonwa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Visual culture is the expression of the norms and social behavior of a society in visual images. A reflection simply shows you how you look when you stand before a mirror, a clear water or stream. The mirror does not alter, improve or distort your original appearance, neither does it show you a caricature of what stands before it, this is the case with visual images created by a tribe or society. The ‘uli’ is hand drawn body design done on Igbo women and speaks of a culture of body adornment which is a practice that is appreciated by that tribe. The use of pattern of the gliding python snake ‘ije eke’ or ‘ijeagwo’ for wall painting speaks of the Igbo culture as one that appreciates wall paintings based on these patterns. Modern life came and brought a lot of change to the Igbo-speaking people of Nigeria. Change cloaked in the garment of Westernization has influenced the culture of the Igbos. This has resulted in a problem which is a break in the cultural practice that has also affected art produced by the Igbos. Before the colonial masters arrived and changed the established culture practiced by the Igbos, visual images were created that retained the culture of this people. To bring this point to limelight, this paper has adopted a historical method. A large number of works produced during pre and post-colonial era which range from sculptural pieces, paintings and other artifacts, just to mention a few, were studied carefully and it was discovered that the visual images hold the culture or aspects of the culture of the Igbos in their renditions and can rightly serve as a mirror of the Igbo visual culture. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artistic%20renditions" title="artistic renditions">artistic renditions</a>, <a href="https://publications.waset.org/abstracts/search?q=historical%20method" title=" historical method"> historical method</a>, <a href="https://publications.waset.org/abstracts/search?q=Igbo%20visual%20culture" title=" Igbo visual culture"> Igbo visual culture</a>, <a href="https://publications.waset.org/abstracts/search?q=changes" title=" changes"> changes</a> </p> <a href="https://publications.waset.org/abstracts/107226/igbo-art-a-reflection-of-the-igbos-visual-culture" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/107226.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">189</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">6207</span> Intelligent Rheumatoid Arthritis Identification System Based Image Processing and Neural Classifier</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdulkader%20Helwan">Abdulkader Helwan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=rheumatoid%20arthritis" title="rheumatoid arthritis">rheumatoid arthritis</a>, <a href="https://publications.waset.org/abstracts/search?q=intelligent%20identification" title=" intelligent identification"> intelligent identification</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20classifier" title=" neural classifier"> neural classifier</a>, <a href="https://publications.waset.org/abstracts/search?q=segmentation" title=" segmentation"> segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=backpropoagation" title=" backpropoagation"> backpropoagation</a> </p> <a href="https://publications.waset.org/abstracts/26123/intelligent-rheumatoid-arthritis-identification-system-based-image-processing-and-neural-classifier" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26123.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">532</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">6206</span> Body Composition Analysis of Wild Labeo Bata in Relation to Body Size and Condition Factor from Chenab, Multan, Pakistan</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Naeem">Muhammad Naeem</a>, <a href="https://publications.waset.org/abstracts/search?q=Amina%20Zubari"> Amina Zubari</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdus%20Salam"> Abdus Salam</a>, <a href="https://publications.waset.org/abstracts/search?q=Syed%20Ali%20Ayub%20Bukhari"> Syed Ali Ayub Bukhari</a>, <a href="https://publications.waset.org/abstracts/search?q=Naveed%20Ahmad%20Khan">Naveed Ahmad Khan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Seventy three wild Labeo bata of different body sizes, ranging from 8.20-16.00 cm total length and 7.4-86.19 g body weight, were studied for the analysis of body composition parameters (Water content, ash content, fat content, protein content) in relation to body size and condition factor. Mean percentage is found as for water 77.71 %, ash 3.42 %, fat 2.20 % and protein content 16.65 % in whole wet body weight. Highly significant positive correlations were observed between condition factor and body weight (r = 0.243). Protein contents, organic content and ash (% wet body weight) increase with increasing percent water contents for Labeo bata while these constituents (% dry body weight) and fat contents (% wet and dry body weight) have no influence on percent water. It was observed that variations in the body constituents have no association to body weight or length. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Labeo%20bata" title="Labeo bata">Labeo bata</a>, <a href="https://publications.waset.org/abstracts/search?q=body%20size" title=" body size"> body size</a>, <a href="https://publications.waset.org/abstracts/search?q=body%20composition" title=" body composition"> body composition</a>, <a href="https://publications.waset.org/abstracts/search?q=condition%20factor" title=" condition factor"> condition factor</a> </p> <a href="https://publications.waset.org/abstracts/20571/body-composition-analysis-of-wild-labeo-bata-in-relation-to-body-size-and-condition-factor-from-chenab-multan-pakistan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20571.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">497</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">6205</span> Exploring the Representations of the Moroccan Female Body on Social Media: YouTube as a Case Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nadir%20Akrachi">Nadir Akrachi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> YouTube is one of the social media platforms that has gained popularity over the last decade. With the use of YouTube channels, young girls are able to post videos about their opinions of the ideal body and beauty and connect to their audience through likes, comments, and shares. In addition, it has become apparent that these young women associate their bodies with the ideal body image. They relate their body to the ideal body aspects that are produced by YouTubers, which causes differences between their body shape and the ideal body. Thus, this has led many researchers to explore whether these social media outlets are influencing the ways women look at their bodies and whether these social media associations cause a negative body image. The purpose of the study is to examine body image perceptions of Moroccan YouTubers. In other words, the study will explore the ways Moroccan YouTubers perceive their body and whether they follow a pattern of objectification or not. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=body%20image" title="body image">body image</a>, <a href="https://publications.waset.org/abstracts/search?q=gender" title=" gender"> gender</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20media" title=" social media"> social media</a>, <a href="https://publications.waset.org/abstracts/search?q=representation" title=" representation"> representation</a>, <a href="https://publications.waset.org/abstracts/search?q=female%20body" title=" female body"> female body</a> </p> <a href="https://publications.waset.org/abstracts/193128/exploring-the-representations-of-the-moroccan-female-body-on-social-media-youtube-as-a-case-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/193128.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">17</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">6204</span> Effective Texture Features for Segmented Mammogram Images Based on Multi-Region of Interest Segmentation Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ramayanam%20Suresh">Ramayanam Suresh</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Nagaraja%20Rao"> A. Nagaraja Rao</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Eswara%20Reddy"> B. Eswara Reddy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Texture features of mammogram images are useful for finding masses or cancer cases in mammography, which have been used by radiologists. Textures are greatly succeeded for segmented images rather than normal images. It is necessary to perform segmentation for exclusive specification of cancer and non-cancer regions separately. Region of interest (ROI) is most commonly used technique for mammogram segmentation. Limitation of this method is that it is unable to explore segmentation for large collection of mammogram images. Therefore, this paper is proposed multi-ROI segmentation for addressing the above limitation. It supports greatly in finding the best texture features of mammogram images. Experimental study demonstrates the effectiveness of proposed work using benchmarked images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=texture%20features" title="texture features">texture features</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=multi-ROI%20segmentation" title=" multi-ROI segmentation"> multi-ROI segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=benchmarked%20images" title=" benchmarked images "> benchmarked images </a> </p> <a href="https://publications.waset.org/abstracts/88666/effective-texture-features-for-segmented-mammogram-images-based-on-multi-region-of-interest-segmentation-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88666.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">311</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" href="https://publications.waset.org/abstracts/search?q=body%20images&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=body%20images&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=body%20images&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=body%20images&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=body%20images&page=6">6</a></li> <li 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