Segmentation of the Liver from Abdominal CT Using Markov Random Field Model and GVF Snakes
Liver segmentation from scans of the abdominal area is an important step in several diagnostic processes. CT scans of the abdominal area contain several organs in close proximity exhibiting similar image characteristics. In this paper, we present preliminary results on an algorithm that uses Markov...
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| creator | Alomari, R.S. Kompalli, S. Chaudhary, V. |
| description | Liver segmentation from scans of the abdominal area is an important step in several diagnostic processes. CT scans of the abdominal area contain several organs in close proximity exhibiting similar image characteristics. In this paper, we present preliminary results on an algorithm that uses Markov random fields to obtain an initial contour of the liver. Gradient vector fields (GVF) and active contours are used to refine the initial estimate and segment the liver. Tests are reported on 13 clinical cases using a similarity metric that combines area and space. |
| doi_str_mv | 10.1109/CISIS.2008.135 |
| format | Conference Proceeding |
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Tests are reported on 13 clinical cases using a similarity metric that combines area and space.</description><subject>Circuit faults</subject><subject>Computed tomography</subject><subject>Current transformers</subject><subject>database construction</subject><subject>evaluation</subject><subject>Fault currents</subject><subject>GVF Snakes</subject><subject>Image segmentation</subject><subject>Liver</subject><subject>liver segmentation</subject><subject>Markov Random Fields</subject><subject>Pixel</subject><subject>X-ray CT</subject><isbn>9780769531090</isbn><isbn>0769531091</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotkD1rwzAURQUl0JB67dLl_QG7kixL1hhMkxocCnXSoUuQ7adUjT-KbQL991VI73LhHLjDJeSR0Ygxqp-zvMzLiFOaRixO7kigVUqV1EnsLV2QJadKC6aZuCfBNH1TnyRJqWBL8lniqcN-NrMbehgszF8IhbvgCHYcOlhXzdC53rSQ7eEwuf4EOzOehwu8m94r2DhsG9gNDbbgCWw_NlD25ozTA1lY004Y_PeKHDYv--w1LN62ebYuQsdZModSaMmUiiXXqkZLhaQiltJIW2GsWU0bxTmrRXXF3ErNK1sbVlXGs8SaeEWebrsOEY8_o-vM-Hv0M_J6wR_xelEu</recordid><startdate>20080101</startdate><enddate>20080101</enddate><creator>Alomari, R.S.</creator><creator>Kompalli, S.</creator><creator>Chaudhary, V.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20080101</creationdate><title>Segmentation of the Liver from Abdominal CT Using Markov Random Field Model and GVF Snakes</title><author>Alomari, R.S. ; Kompalli, S. ; Chaudhary, V.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i215t-649617736297cef04604366a6fbe391c0d7221c4b04362f692bfca1bbac4b5fa3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Circuit faults</topic><topic>Computed tomography</topic><topic>Current transformers</topic><topic>database construction</topic><topic>evaluation</topic><topic>Fault currents</topic><topic>GVF Snakes</topic><topic>Image segmentation</topic><topic>Liver</topic><topic>liver segmentation</topic><topic>Markov Random Fields</topic><topic>Pixel</topic><topic>X-ray CT</topic><toplevel>online_resources</toplevel><creatorcontrib>Alomari, R.S.</creatorcontrib><creatorcontrib>Kompalli, S.</creatorcontrib><creatorcontrib>Chaudhary, V.</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>Alomari, R.S.</au><au>Kompalli, S.</au><au>Chaudhary, V.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Segmentation of the Liver from Abdominal CT Using Markov Random Field Model and GVF Snakes</atitle><btitle>2008 International Conference on Complex, Intelligent and Software Intensive Systems</btitle><stitle>CISIS</stitle><date>2008-01-01</date><risdate>2008</risdate><spage>293</spage><epage>298</epage><pages>293-298</pages><isbn>9780769531090</isbn><isbn>0769531091</isbn><abstract>Liver segmentation from scans of the abdominal area is an important step in several diagnostic processes. CT scans of the abdominal area contain several organs in close proximity exhibiting similar image characteristics. In this paper, we present preliminary results on an algorithm that uses Markov random fields to obtain an initial contour of the liver. Gradient vector fields (GVF) and active contours are used to refine the initial estimate and segment the liver. Tests are reported on 13 clinical cases using a similarity metric that combines area and space.</abstract><pub>IEEE</pub><doi>10.1109/CISIS.2008.135</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Circuit faults Computed tomography Current transformers database construction evaluation Fault currents GVF Snakes Image segmentation Liver liver segmentation Markov Random Fields Pixel X-ray CT |
| title | Segmentation of the Liver from Abdominal CT Using Markov Random Field Model and GVF Snakes |
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