Search results for: G. Raso

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Raso</title> <meta name="description" content="Search results for: G. Raso"> <meta name="keywords" content="G. Raso"> <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 ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="G. 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Raso"> <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> 2</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: G. Raso</h1> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Massive Lesions Classification using Features based on Morphological Lesion Differences</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=U.%20Bottigli">U. Bottigli</a>, <a href="https://publications.waset.org/search?q=D.Cascio"> D.Cascio</a>, <a href="https://publications.waset.org/search?q=F.%20Fauci"> F. Fauci</a>, <a href="https://publications.waset.org/search?q=B.%20Golosio"> B. Golosio</a>, <a href="https://publications.waset.org/search?q=R.%20Magro"> R. Magro</a>, <a href="https://publications.waset.org/search?q=G.L.%20Masala"> G.L. Masala</a>, <a href="https://publications.waset.org/search?q=P.%20Oliva"> P. Oliva</a>, <a href="https://publications.waset.org/search?q=G.%20Raso"> G. Raso</a>, <a href="https://publications.waset.org/search?q=S.Stumbo"> S.Stumbo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based on morphological lesion differences. Some classifiers as a Feed Forward Neural Network, a K-Nearest Neighbours and a Support Vector Machine are used to distinguish the pathological records from the healthy ones. The results obtained in terms of sensitivity (percentage of pathological ROIs correctly classified) and specificity (percentage of non-pathological ROIs correctly classified) will be presented through the Receive Operating Characteristic curve (ROC). In particular the best performances are 88% 卤 1 of area under ROC curve obtained with the Feed Forward Neural Network. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Neural%20Networks" title="Neural Networks">Neural Networks</a>, <a href="https://publications.waset.org/search?q=K-Nearest%20Neighbours" title=" K-Nearest Neighbours"> K-Nearest Neighbours</a>, <a href="https://publications.waset.org/search?q=SupportVector%20Machine" title=" SupportVector Machine"> SupportVector Machine</a>, <a href="https://publications.waset.org/search?q=Computer%20Aided%20Diagnosis." title=" Computer Aided Diagnosis."> Computer Aided Diagnosis.</a> </p> <a href="https://publications.waset.org/14762/massive-lesions-classification-using-features-based-on-morphological-lesion-differences" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/14762/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/14762/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/14762/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/14762/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/14762/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/14762/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/14762/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/14762/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/14762/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/14762/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/14762.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">1391</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Superior Performances of the Neural Network on the Masses Lesions Classification through Morphological Lesion Differences</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=U.%20Bottigli">U. Bottigli</a>, <a href="https://publications.waset.org/search?q=R.Chiarucci"> R.Chiarucci</a>, <a href="https://publications.waset.org/search?q=B.%20Golosio"> B. Golosio</a>, <a href="https://publications.waset.org/search?q=G.L.%20Masala"> G.L. Masala</a>, <a href="https://publications.waset.org/search?q=P.%20Oliva"> P. Oliva</a>, <a href="https://publications.waset.org/search?q=S.Stumbo"> S.Stumbo</a>, <a href="https://publications.waset.org/search?q=D.Cascio"> D.Cascio</a>, <a href="https://publications.waset.org/search?q=F.%20Fauci"> F. Fauci</a>, <a href="https://publications.waset.org/search?q=M.%20Glorioso"> M. Glorioso</a>, <a href="https://publications.waset.org/search?q=M.%20Iacomi"> M. Iacomi</a>, <a href="https://publications.waset.org/search?q=R.%20Magro"> R. Magro</a>, <a href="https://publications.waset.org/search?q=G.%20Raso"> G. Raso</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be presented through the ROC (Receiver Operating Characteristic) curves. In particular the best performances are obtained with the Neural Networks in comparison with the K-Nearest Neighbours and the Support Vector Machine: The Radial Basis Function supply the best results with 0.89 ± 0.01 of area under ROC curve but similar results are obtained with the Probabilistic Neural Network and a Multi Layer Perceptron.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Neural%20Networks" title="Neural Networks">Neural Networks</a>, <a href="https://publications.waset.org/search?q=K-Nearest%20Neighbours" title=" K-Nearest Neighbours"> K-Nearest Neighbours</a>, <a href="https://publications.waset.org/search?q=Support%20Vector%20Machine" title=" Support Vector Machine"> Support Vector Machine</a>, <a href="https://publications.waset.org/search?q=Computer%20Aided%20Detection" title=" Computer Aided Detection"> Computer Aided Detection</a> </p> <a href="https://publications.waset.org/1568/superior-performances-of-the-neural-network-on-the-masses-lesions-classification-through-morphological-lesion-differences" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/1568/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/1568/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/1568/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/1568/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/1568/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/1568/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a 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Search results for: G. Raso