Robust Segmentation of Salient Features in Automatic Breast Ultrasound (ABUS) Images

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Features in Automatic Breast Ultrasound (ABUS) Images</title> <meta name="description" content="Robust Segmentation of Salient Features in Automatic Breast Ultrasound (ABUS) Images"> <meta name="keywords" content="Automated 3D Breast Ultrasound, Eigenvalues of Hessian matrix, Nipple detection, Rib detection"> <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 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publication-listing mt-3 mb-3"> <h5 class="card-header" style="font-size:.9rem">Robust Segmentation of Salient Features in Automatic Breast Ultrasound (ABUS) Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lamees%20Nasser">Lamees Nasser</a>, <a href="https://publications.waset.org/abstracts/search?q=Yago%20Diez"> Yago Diez</a>, <a href="https://publications.waset.org/abstracts/search?q=Robert%20Mart%C3%AD"> Robert Mart铆</a>, <a href="https://publications.waset.org/abstracts/search?q=Joan%20Mart%C3%AD"> Joan Mart铆</a>, <a href="https://publications.waset.org/abstracts/search?q=Ibrahim%20Sadek"> Ibrahim Sadek</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Automated 3D breast ultrasound (ABUS) screening is a novel modality in medical imaging because of its common characteristics shared with other ultrasound modalities in addition to the three orthogonal planes (i.e., axial, sagittal, and coronal) that are useful in analysis of tumors. In the literature, few automatic approaches exist for typical tasks such as segmentation or registration. In this work, we deal with two problems concerning ABUS images: nipple and rib detection. Nipple and ribs are the most visible and salient features in ABUS images. Determining the nipple position plays a key role in some applications for example evaluation of registration results or lesion follow-up. We present a nipple detection algorithm based on color and shape of the nipple, besides an automatic approach to detect the ribs. In point of fact, rib detection is considered as one of the main stages in chest wall segmentation. This approach consists of four steps. First, images are normalized in order to minimize the intensity variability for a given set of regions within the same image or a set of images. Second, the normalized images are smoothed by using anisotropic diffusion filter. Next, the ribs are detected in each slice by analyzing the eigenvalues of the 3D Hessian matrix. Finally, a breast mask and a probability map of regions detected as ribs are used to remove false positives (FP). Qualitative and quantitative evaluation obtained from a total of 22 cases is performed. For all cases, the average and standard deviation of the root mean square error (RMSE) between manually annotated points placed on the rib surface and detected points on rib borders are 15.1188 mm and 14.7184 mm respectively. <iframe src="https://publications.waset.org/abstracts/41104.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Automated%203D%20Breast%20Ultrasound" title="Automated 3D Breast Ultrasound">Automated 3D Breast Ultrasound</a>, <a href="https://publications.waset.org/abstracts/search?q=Eigenvalues%20of%20Hessian%20matrix" title=" Eigenvalues of Hessian matrix"> Eigenvalues of Hessian matrix</a>, <a href="https://publications.waset.org/abstracts/search?q=Nipple%20detection" title=" Nipple detection"> Nipple detection</a>, <a href="https://publications.waset.org/abstracts/search?q=Rib%20detection" title=" Rib detection"> Rib detection</a> </p> <a href="https://publications.waset.org/abstracts/41104/robust-segmentation-of-salient-features-in-automatic-breast-ultrasound-abus-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41104.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">330</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div 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Robust Segmentation of Salient Features in Automatic Breast Ultrasound (ABUS) Images