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Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier
<!DOCTYPE html> <html lang="en" dir="ltr"> <head> <!-- Google tag (gtag.js) --> <script async src="https://www.googletagmanager.com/gtag/js?id=G-P63WKM1TM1"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-P63WKM1TM1'); </script> <!-- Yandex.Metrika counter --> <script type="text/javascript" > (function(m,e,t,r,i,k,a){m[i]=m[i]||function(){(m[i].a=m[i].a||[]).push(arguments)}; m[i].l=1*new Date(); for (var j = 0; j < document.scripts.length; j++) {if (document.scripts[j].src === r) { return; }} k=e.createElement(t),a=e.getElementsByTagName(t)[0],k.async=1,k.src=r,a.parentNode.insertBefore(k,a)}) (window, document, "script", "https://mc.yandex.ru/metrika/tag.js", "ym"); ym(55165297, "init", { clickmap:false, trackLinks:true, accurateTrackBounce:true, webvisor:false }); </script> <noscript><div><img src="https://mc.yandex.ru/watch/55165297" style="position:absolute; left:-9999px;" alt="" /></div></noscript> <!-- /Yandex.Metrika counter --> <!-- Matomo --> <!-- End Matomo Code --> <title>Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier</title> <meta name="description" content="Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier"> <meta name="keywords" content="Artificial neural network, ANN, brain tumor, computer-aided diagnostic, CAD system, gray-level co-occurrence matrix, GLCM, level set method, tumor segmentation."> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <meta name="citation_title" content="Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier"> <meta name="citation_author" content="Atanu K Samanta"> <meta name="citation_author" content="Asim Ali Khan"> <meta name="citation_publication_date" content="2017/04/01"> <meta name="citation_journal_title" content="International Journal of Biomedical and Biological Engineering"> <meta name="citation_volume" content="11"> <meta name="citation_issue" content="6"> <meta name="citation_firstpage" content="340"> <meta name="citation_lastpage" content="347"> <meta name="citation_pdf_url" content="https://publications.waset.org/10007245/pdf"> <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 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Count:</strong> 33093</div> </div> </div> </div> <div class="card publication-listing mt-3 mb-3"> <h5 class="card-header" style="font-size:.9rem">Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Atanu%20K%20Samanta">Atanu K Samanta</a>, <a href="https://publications.waset.org/search?q=Asim%20Ali%20Khan"> Asim Ali Khan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.</p> <iframe src="https://publications.waset.org/10007245.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Artificial%20neural%20network" title="Artificial neural network">Artificial neural network</a>, <a href="https://publications.waset.org/search?q=ANN" title=" ANN"> ANN</a>, <a href="https://publications.waset.org/search?q=brain%20tumor" title=" brain tumor"> brain tumor</a>, <a href="https://publications.waset.org/search?q=computer-aided%20diagnostic" title=" computer-aided diagnostic"> computer-aided diagnostic</a>, <a href="https://publications.waset.org/search?q=CAD%20system" title=" CAD system"> CAD system</a>, <a href="https://publications.waset.org/search?q=gray-level%20co-occurrence%20matrix" title=" gray-level co-occurrence matrix"> gray-level co-occurrence matrix</a>, <a href="https://publications.waset.org/search?q=GLCM" title=" GLCM"> GLCM</a>, <a href="https://publications.waset.org/search?q=level%20set%20method" title=" level set method"> level set method</a>, <a href="https://publications.waset.org/search?q=tumor%20segmentation." title=" tumor segmentation."> tumor segmentation.</a> </p> <p class="card-text"><strong>Digital Object Identifier (DOI):</strong> <a href="https://doi.org/10.5281/zenodo.1130735" target="_blank">doi.org/10.5281/zenodo.1130735</a> </p> <a href="https://publications.waset.org/10007245/computer-aided-diagnostic-system-for-detection-and-classification-of-a-brain-tumor-through-mri-using-level-set-based-segmentation-technique-and-ann-classifier" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10007245/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10007245/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10007245/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10007245/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10007245/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10007245/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10007245/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10007245/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10007245/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10007245/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10007245.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">1365</span> </span> <p class="card-text"><strong>References:</strong></p> <br>[1] The Essential Guide to Brain Tumors, National Brain Tumor Society, http://www.braintumor.org <br>[2] A. Drevelegas (ed.), “Imaging of Brain Tumors with Histological Correlations,” Springer-Verlag Berlin Heidelberg 2011. <br>[3] El-Sayed A. El-Dahshan et al. “Computer-Aided Diagnosis of Human Brain Tumor through MRI: A Survey and a New Algorithm,” Expert Systems with Applications, 41 (2014), 5526–5545. <br>[4] Jainy Sachdeva et al. “A Novel Content-Based Active Contour Model for Brain Tumor Segmentation,” Magnetic Resonance Imaging, 30 (2012), 694–715. <br>[5] Stephen M. Smith, “Fast Robust Automated Brain Extraction,” Human Brain Mapping, 17:143–155(2002). <br>[6] K. Somasundaram, T. 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