A new computer-aided detection system for pulmonary nodules
Computer-aided detection (CAD) systems can help radiologists in early stage diagnosing of lung abnormalities. In this study, a new CAD system is presented by using wavelet transform for pulmonary nodule detection. Classification is performed by using kernels of support vector machines. Results are c...
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creator | Tartar, A. Kilic, N. Olgun, D. C. Akan, A. |
description | Computer-aided detection (CAD) systems can help radiologists in early stage diagnosing of lung abnormalities. In this study, a new CAD system is presented by using wavelet transform for pulmonary nodule detection. Classification is performed by using kernels of support vector machines. Results are compared to similar works in the literature. Proposed CAD system results in 82.1% sensitivity. |
doi_str_mv | 10.1109/SIU.2013.6531293 |
format | Conference Proceeding |
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Proposed CAD system results in 82.1% sensitivity.</description><subject>CAD system</subject><subject>Computed tomography</subject><subject>Design automation</subject><subject>Graphics</subject><subject>Kernel</subject><subject>Lungs</subject><subject>Medical diagnostic imaging</subject><subject>pattern recognition</subject><subject>Pulmonary nodule</subject><subject>support vector machine</subject><subject>wavelet transform</subject><isbn>9781467355629</isbn><isbn>1467355623</isbn><isbn>9781467355636</isbn><isbn>1467355631</isbn><isbn>1467355615</isbn><isbn>9781467355612</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVj81Lw0AUxFdEUGrugpf9B1Lf25e8zeKpFD8KBQ_ac9lmXyCSL7IJ0v_egL14GmZght8o9YCwRgT39Lk7rA0grTknNI6uVOJsgRlbynMmvv7njbtVSYzfALC02RV8p543upMfXfbtME8ypr4OEnSQScqp7jsdz3GSVlf9qIe5afvOj2fd9WFuJN6rm8o3UZKLrtTh9eVr-57uP952280-rRHyKWXJjMUqo9KKrdiTC9YHCPZECxqFgjjHzBsL4L09QRDhAGi5WGIjSCv1-Ldbi8hxGOt2gTheLtMvkYxIqw</recordid><startdate>201304</startdate><enddate>201304</enddate><creator>Tartar, A.</creator><creator>Kilic, N.</creator><creator>Olgun, D. 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C. ; Akan, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i105t-6e4271f43c7e7f6a39d7ad0d7b38143d836514a2700aa7b0dee6d017685142e13</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng ; tur</language><creationdate>2013</creationdate><topic>CAD system</topic><topic>Computed tomography</topic><topic>Design automation</topic><topic>Graphics</topic><topic>Kernel</topic><topic>Lungs</topic><topic>Medical diagnostic imaging</topic><topic>pattern recognition</topic><topic>Pulmonary nodule</topic><topic>support vector machine</topic><topic>wavelet transform</topic><toplevel>online_resources</toplevel><creatorcontrib>Tartar, A.</creatorcontrib><creatorcontrib>Kilic, N.</creatorcontrib><creatorcontrib>Olgun, D. C.</creatorcontrib><creatorcontrib>Akan, A.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Tartar, A.</au><au>Kilic, N.</au><au>Olgun, D. C.</au><au>Akan, A.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A new computer-aided detection system for pulmonary nodules</atitle><btitle>2013 21st Signal Processing and Communications Applications Conference (SIU)</btitle><stitle>SIU</stitle><date>2013-04</date><risdate>2013</risdate><spage>1</spage><epage>4</epage><pages>1-4</pages><isbn>9781467355629</isbn><isbn>1467355623</isbn><eisbn>9781467355636</eisbn><eisbn>1467355631</eisbn><eisbn>1467355615</eisbn><eisbn>9781467355612</eisbn><abstract>Computer-aided detection (CAD) systems can help radiologists in early stage diagnosing of lung abnormalities. In this study, a new CAD system is presented by using wavelet transform for pulmonary nodule detection. Classification is performed by using kernels of support vector machines. Results are compared to similar works in the literature. Proposed CAD system results in 82.1% sensitivity.</abstract><pub>IEEE</pub><doi>10.1109/SIU.2013.6531293</doi><tpages>4</tpages></addata></record> |
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subjects | CAD system Computed tomography Design automation Graphics Kernel Lungs Medical diagnostic imaging pattern recognition Pulmonary nodule support vector machine wavelet transform |
title | A new computer-aided detection system for pulmonary nodules |
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