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A novel approach to computer-aided diagnosis of mammographic images
The article is a work-in-progress report of a research endeavor that deals with the design and development of a novel approach to computer aided diagnosis (CAD) of mammographic images. With the initial emphasis being on the analysis of microcalcifications, the proposed approach defines a synergistic...
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creator | Sari-Sarraf, H. Gleason, S.S. Hudson, K.T. Hubner, K.F. |
description | The article is a work-in-progress report of a research endeavor that deals with the design and development of a novel approach to computer aided diagnosis (CAD) of mammographic images. With the initial emphasis being on the analysis of microcalcifications, the proposed approach defines a synergistic paradigm that utilizes new methodologies together with previously developed techniques. The new paradigm is intended to promote a higher degree of accuracy in CAD of mammograms with an increased overall throughput. The process of accomplishing these goals is initiated by the fractal encoding of the input image, which gives rise to the generation of focus-of-attention regions (FARs), that is, regions that contain anomalies. The primary thrust of this work is to demonstrate that by considering FARs, rather than the entire input image, the performances of the ensuing processes (i.e., segmentation, feature extraction, and classification) are enhanced in terms of accuracy and speed. An experimental study is included that demonstrates the impact of FAR generation on the process of microcalcification segmentation. |
doi_str_mv | 10.1109/ACV.1996.572060 |
format | conference_proceeding |
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With the initial emphasis being on the analysis of microcalcifications, the proposed approach defines a synergistic paradigm that utilizes new methodologies together with previously developed techniques. The new paradigm is intended to promote a higher degree of accuracy in CAD of mammograms with an increased overall throughput. The process of accomplishing these goals is initiated by the fractal encoding of the input image, which gives rise to the generation of focus-of-attention regions (FARs), that is, regions that contain anomalies. The primary thrust of this work is to demonstrate that by considering FARs, rather than the entire input image, the performances of the ensuing processes (i.e., segmentation, feature extraction, and classification) are enhanced in terms of accuracy and speed. 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The primary thrust of this work is to demonstrate that by considering FARs, rather than the entire input image, the performances of the ensuing processes (i.e., segmentation, feature extraction, and classification) are enhanced in terms of accuracy and speed. An experimental study is included that demonstrates the impact of FAR generation on the process of microcalcification segmentation.</description><subject>Biomedical imaging</subject><subject>Breast cancer</subject><subject>Computer aided diagnosis</subject><subject>Design automation</subject><subject>Focusing</subject><subject>Fractals</subject><subject>Image segmentation</subject><subject>Laboratories</subject><subject>Medical diagnostic imaging</subject><subject>Throughput</subject><isbn>9780818676208</isbn><isbn>0818676205</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1996</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj8tqwzAURAWl0JJ6HehKP2D3SrL1WBrTFwSyabMN15LsqMSRkdxC_76GdDYDZzGHIWTLoGIMzFPbHSpmjKwaxUHCDSmM0qCZlkpy0HekyPkL1tRCMSPuSdfSS_zxZ4rznCLaE10itXGavxefSgzOO-oCjpeYQ6ZxoBNOUxwTzqdgaZhw9PmB3A54zr747w35fHn-6N7K3f71vWt3ZWB1s5TcalBCgXG9M9gI5YxeUSN65NoPjteWgxi8YY0ErCX0tXXC9INF6aSQYkMer7vBe3-c02pPv8frU_EHt9RIsQ</recordid><startdate>1996</startdate><enddate>1996</enddate><creator>Sari-Sarraf, H.</creator><creator>Gleason, S.S.</creator><creator>Hudson, K.T.</creator><creator>Hubner, K.F.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1996</creationdate><title>A novel approach to computer-aided diagnosis of mammographic images</title><author>Sari-Sarraf, H. ; Gleason, S.S. ; Hudson, K.T. ; Hubner, K.F.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i145t-2c8073709dbd9a537d98c8053ba28efd24c203fe91560a460b4cd39bfca6d6363</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1996</creationdate><topic>Biomedical imaging</topic><topic>Breast cancer</topic><topic>Computer aided diagnosis</topic><topic>Design automation</topic><topic>Focusing</topic><topic>Fractals</topic><topic>Image segmentation</topic><topic>Laboratories</topic><topic>Medical diagnostic imaging</topic><topic>Throughput</topic><toplevel>online_resources</toplevel><creatorcontrib>Sari-Sarraf, H.</creatorcontrib><creatorcontrib>Gleason, S.S.</creatorcontrib><creatorcontrib>Hudson, K.T.</creatorcontrib><creatorcontrib>Hubner, K.F.</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</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>Sari-Sarraf, H.</au><au>Gleason, S.S.</au><au>Hudson, K.T.</au><au>Hubner, K.F.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A novel approach to computer-aided diagnosis of mammographic images</atitle><btitle>Proceedings Third IEEE Workshop on Applications of Computer Vision. 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The primary thrust of this work is to demonstrate that by considering FARs, rather than the entire input image, the performances of the ensuing processes (i.e., segmentation, feature extraction, and classification) are enhanced in terms of accuracy and speed. An experimental study is included that demonstrates the impact of FAR generation on the process of microcalcification segmentation.</abstract><pub>IEEE</pub><doi>10.1109/ACV.1996.572060</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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identifier | ISBN: 9780818676208 |
ispartof | Proceedings Third IEEE Workshop on Applications of Computer Vision. WACV'96, 1996, p.230-235 |
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language | eng |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Biomedical imaging Breast cancer Computer aided diagnosis Design automation Focusing Fractals Image segmentation Laboratories Medical diagnostic imaging Throughput |
title | A novel approach to computer-aided diagnosis of mammographic images |
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