GLAUCOMA DISEASE DIAGNOSIS USING FEED FORWARD NEURAL NETWORK

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This optic disorder with a gradual loss of the field of vision leads to progressive and irreversible blindness, so it should be diagnosed and treated properly at an early stage. In this paper, thedaubechies(db3) or symlets (sym3)and reverse biorthogonal (rbio3.7) wavelet filters are employed for obtaining average and energy texture feature which are used to classify glaucoma disease with high accuracy. The Feed-Forward neural network classifies the glaucoma disease with an accuracy of 96.67%. In this work, the computational complexity is minimized by reducing the number of filters while retaining the same accuracy."/> <meta name="keywords" content="Glaucoma, IOP, Wavelet transform, Texture features, Feed Forward neural network, Fundus images"/>   <meta name="dc.title" content="GLAUCOMA DISEASE DIAGNOSIS USING FEED FORWARD NEURAL NETWORK"> <meta name="citation_author" content="Ch. P. Poojitha"> <meta name="citation_author" content="B. Nalini"> <meta name="citation_author" content="Dr.N. Balaji"> <meta name="dc.type" content="Article"> <meta name="dc.source" content="International Journal on Cybernetics & Informatics (IJCI), Vol 5, No.4"> <meta name="dc.date" content="2016/08/30"> <meta name="dc.identifier" content="10.5121/ijci.2016.5417"> <meta name="dc.publisher" content="AIRCC Publishing Corporation"> <meta name="dc.rights" content="http://creativecommons.org/licenses/by/3.0/"> <meta name="dc.format" content="application/pdf"> <meta name="dc.language" content="en"> <meta name="dc.description" content="Glaucoma is an eye disease which damages the optic nerve and or loss of the field of vision which leads to complete blindness caused by the pressure buildup by the fluid of the eye i.e. the intraocular pressure (IOP). This optic disorder with a gradual loss of the field of vision leads to progressive and irreversible blindness, so it should be diagnosed and treated properly at an early stage. In this paper, thedaubechies(db3) or symlets (sym3)and reverse biorthogonal (rbio3.7) wavelet filters are employed for obtaining average and energy texture feature which are used to classify glaucoma disease with high accuracy. The Feed-Forward neural network classifies the glaucoma disease with an accuracy of 96.67%. In this work, the computational complexity is minimized by reducing the number of filters while retaining the same accuracy."/> <meta name="dc.subject" content="Glaucoma"> <meta name="dc.subject" content=" IOP"> <meta name="dc.subject" content="Wavelet transform"> <meta name="dc.subject" content="Texture features"> <meta name="dc.subject" content="Feed Forward neural network"> <meta name="dc.subject" content="Fundus images">   <meta name="prism.publicationName" content="International Journal on Cybernetics & Informatics (IJCI)"> <meta name="prism.publicationDate" content="2016/08/30"> <meta name="prism.volume" content="5"> <meta name="prism.number" content="4"> <meta name="prism.section" content="Article"> <meta name="prism.startingPage" content="149">   <meta name="citation_journal_title" content="International Journal on Cybernetics & Informatics (IJCI)"> <meta name="citation_publisher" content="AIRCC Publishing Corporation"> <meta name="citation_authors" content="Ch. P. Poojitha;B. 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Balaji"> <meta name="citation_doi" content="10.5121/ijci.2016.5417"> <meta name="citation_abstract_html_url" content="https://ijcionline.com/abstract/5416ijci17"> <meta name="citation_pdf_url" content="https://aircconline.com/ijci/V5N4/5416ijci17.pdf">   <meta property="og:site_name" content="AIRCC" /> <meta property="og:type" content="article" /> <meta property="og:url" content="https://ijcionline.com/abstract/5416ijci17"/> <meta property="og:title" content="Glaucoma is an eye disease which damages the optic nerve and or loss of the field of vision which leads to complete blindness caused by the pressure buildup by the fluid of the eye i.e. the intraocular pressure (IOP). This optic disorder with a gradual loss of the field of vision leads to progressive and irreversible blindness, so it should be diagnosed and treated properly at an early stage. In this paper, thedaubechies(db3) or symlets (sym3)and reverse biorthogonal (rbio3.7) wavelet filters are employed for obtaining average and energy texture feature which are used to classify glaucoma disease with high accuracy. The Feed-Forward neural network classifies the glaucoma disease with an accuracy of 96.67%. In this work, the computational complexity is minimized by reducing the number of filters while retaining the same accuracy."/>   <meta name="google-site-verification" content="t8rHIcM8EfjIqfQzQ0IdYIiA9JxDD0uUZAitBCzsOIw" /> <meta name="yandex-verification" content="e3d2d5a32c7241f4" />  </head> <body> <div class="navbar-fixed"> <nav class="cyan lighten-2 z-depth-5"> <div class="container"> <div class="nav-wrapper"> <ul> <li id="b-logo"> <img id="brand-logo" href="/index" class="hide-on-med-and-down" src="/img/aircc-logo1.jpg" width="60" height="60" style="vertical-align:middle"> </li> </ul> <a class="brand-logo " href="/index"><h5>IJCI <span class="hide-on-med-and-down">Conference Proceedings</span></h5></a> <a data-activates="side-nav" class="button-collapse show-on-small left"> <i class="material-icons">menu</i> </a> <ul class="right hide-on-med-and-down"> <li class=""> <a href="/index">Home</a> </li> <li class=""> <a href="/volume13">Current issue</a> </li> <li> <a href="/archives">Archives</a> </li> <li class=""> <a href="/contact">Contact</a> </li> </ul> </div> </div> </nav> </div>  <ul class="side-nav" id="side-nav"> <li> <div class="user-view arc"> <div class="background"> <img class="mobile-overlay" > </div> <a href="/index"> <i id="cl" class="material-icons cyan-text text-lighten-2 right">close</i> </a> <a href="/index"> <img class="circle" src="/img/aircc-logo1.jpg"> </a> <h5 class="">IJCI Conference Proceedings</h5> </div> </li> <li class=""> <a href="/index">Home <i class="fas fa-user"></i> </a> </li> <li class=""> <a href="/volume13">Current issue <i class="fas fa-user"></i> </a> </li> <li> <a href="/archives">Archives <i class="fas fa-user"></i> </a> </li> <li class=""> <a href="/contact">Contact <i class="fas fa-user"></i> </a> </li> </ul> <div class="fixed-action-btn" id="scrollTop"> <a class="btn btn-small btn-floating waves-effect waves-light blue lighten-1 pulse" onclick="topFunction()"> <i class="material-icons">keyboard_arrow_up</i> </a> </div>  <section class="section-main" > <div class="container"> <div class="row"> <div class="col s12 m9">  <div class="card z-depth-2"> <div class="card-content"> <h5 class="cyan-text center text-darken-1"> GLAUCOMA DISEASE DIAGNOSIS USING FEED FORWARD NEURAL NETWORK </h5> </div> </div> <br> <div class="card"> <h5 id="about" class="brown-text text-darken-2 text-center" style="padding-bottom:0px">Authors</h5>  <div class="card-content"> <p class="left-text" style="text-align:justify"> Ch. P. Poojitha, B. Nalini and Dr.N. Balaji <br>Jawaharlal Nehru Technological University, India</br> </p> </div> </div>   <div class="card"> <h5 id="about" class="brown-text text-darken-2 text-center" style="padding-bottom:0px">Abstract</h5>  <div class="card-content"> <p class="left-text" style="text-align:justify"> Glaucoma is an eye disease which damages the optic nerve and or loss of the field of vision which leads to complete blindness caused by the pressure buildup by the fluid of the eye i.e. the intraocular pressure (IOP). This optic disorder with a gradual loss of the field of vision leads to progressive and irreversible blindness, so it should be diagnosed and treated properly at an early stage. In this paper, thedaubechies(db3) or symlets (sym3)and reverse biorthogonal (rbio3.7) wavelet filters are employed for obtaining average and energy texture feature which are used to classify glaucoma disease with high accuracy. The Feed-Forward neural network classifies the glaucoma disease with an accuracy of 96.67%. In this work, the computational complexity is minimized by reducing the number of filters while retaining the same accuracy. </p> </div> </div> <div class="card"> <h5 id="about" class="brown-text text-darken-2 text-center" style="padding-bottom:0px">Keywords</h5>  <div class="card-content"> <p class="left-text" style="text-align:justify"> Glaucoma, IOP, Wavelet transform, Texture features, Feed Forward neural network, Fundus images </p> </div> </div> <div class="card-content"> <a href="https://aircconline.com/ijci/V5N4/5416ijci17.pdf" target="blank" class="btn btn-small lighten-2 cyan lig">Full Text</a>  <a href="https://ijcionline.com/vol5" class="btn btn-small lighten-2 cyan lig">Volume 5</a> </div> </div>  <div id="side-bar" class="col s12 m3"> <div id="section-main"> <br> <br> <div class="card side cyan lighten-2"> <div class="card-content"> <ul> <li class="ax waves-effect waves-light"> <a class="white-text" href="/editorial" > <i class="material-icons left">account_circle</i>Editorial Board</a> <br> </li> <br> <br> <div class="divider"></div> <br> <li class="ax waves-effect waves-light"> <a class="white-text" href="/mostcitedarticels" > <i class="material-icons left">book</i>Most Cited Articels </a> <br> </li> <br> <br> <div class="divider"></div> <br> <li class="ax waves-effect waves-light"> <a class="white-text" href="/indexing" > <i class="material-icons left">list</i>Indexing </a> <br> </li> <br> <br> <div class="divider"></div> <br> <li class="ax waves-effect waves-light"> <a class="white-text" href="/faq" > <i class="material-icons left">help</i>FAQ </a> <br> </li> <br> <br> <div class="divider"></div> <br> </div> </div> </div> </div> </div> </div> </div> </section> <br> <br> <br> <br> <div id="txtcnt"></div>  <footer class="page-footer cyan lighten-3"> <div class="nav-wrapper"> <div class="container"> <ul> <li> <a target="_blank" href="http://airccse.org/"> <img src="/img/since2008.png" alt="since2008"></a> </li> </ul> <h6> Free Open Access Conference Proceedings <br> Computer Science & Engineering - Information Technology - Information Systems</h6> </div> <div class="footer-m col m3 s12 offset-m1"> </div> <div class="social col m3 offset-m1 s12"> </div> </div> </div> <div class="col s12 m10 offset-m1"> <div class="grey darken-3 center-align"> <small class="white-text">Designed and Developed by NNN Team</small> </div> </div> </footer> </body>  <script type="text/javascript" src="https://code.jquery.com/jquery-3.2.1.min.js"></script> <script type="text/javascript" src="/js/materialize.min.js"></script> <script src="/js/search.js"></script> <script src="/js/scrolltop.js"></script> <script src="/js/popup.js"></script> <script src="/js/main.jquery.js"></script> </html>

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GLAUCOMA DISEASE DIAGNOSIS USING FEED FORWARD NEURAL NETWORK