Employing temporal information for cell segmentation using max-flow/min-cut in phase-contrast video microscopy
Cell segmentation is a crucial step in many biomedical image analysis applications and it can be considered as an important part of a tracking system. Segmentation in phase-contrast images is a challenging task since in this imaging technique, the background intensity is approximately similar to the...
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| creator | Massoudi, A. Sowmya, A. Mele, K. Semenovich, D. |
| description | Cell segmentation is a crucial step in many biomedical image analysis applications and it can be considered as an important part of a tracking system. Segmentation in phase-contrast images is a challenging task since in this imaging technique, the background intensity is approximately similar to the cell pixel intensity. In this paper we propose an interactive automatic pixel level segmentation algorithm, that uses temporal information to improve the segmentation result. This algorithm is based on the max-flow/min-cut algorithm and can be solved in polynomial time. This method is not restricted to any specific cell shape and segments cells of various shapes and sizes. The results of the proposed algorithm show that using the temporal information does improve segmentation considerably. |
| doi_str_mv | 10.1109/IEMBS.2011.6091479 |
| format | Conference Proceeding |
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Segmentation in phase-contrast images is a challenging task since in this imaging technique, the background intensity is approximately similar to the cell pixel intensity. In this paper we propose an interactive automatic pixel level segmentation algorithm, that uses temporal information to improve the segmentation result. This algorithm is based on the max-flow/min-cut algorithm and can be solved in polynomial time. This method is not restricted to any specific cell shape and segments cells of various shapes and sizes. 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Segmentation in phase-contrast images is a challenging task since in this imaging technique, the background intensity is approximately similar to the cell pixel intensity. In this paper we propose an interactive automatic pixel level segmentation algorithm, that uses temporal information to improve the segmentation result. This algorithm is based on the max-flow/min-cut algorithm and can be solved in polynomial time. This method is not restricted to any specific cell shape and segments cells of various shapes and sizes. The results of the proposed algorithm show that using the temporal information does improve segmentation considerably.</description><subject>Algorithms</subject><subject>Biomedical imaging</subject><subject>Cell Tracking - methods</subject><subject>Image edge detection</subject><subject>Image Enhancement - methods</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Image segmentation</subject><subject>Microscopy</subject><subject>Microscopy, Phase-Contrast - methods</subject><subject>Microscopy, Video - methods</subject><subject>Models, Biological</subject><subject>Object segmentation</subject><subject>Pattern Recognition, Automated - methods</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Shape</subject><subject>Subtraction Technique</subject><issn>1094-687X</issn><issn>1557-170X</issn><issn>1558-4615</issn><isbn>9781424441211</isbn><isbn>1424441218</isbn><isbn>1424441226</isbn><isbn>1457715899</isbn><isbn>9781457715891</isbn><isbn>9781424441228</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><sourceid>EIF</sourceid><recordid>eNo9UEtOwzAQNT_RUnoBkFAu4Nbj2E68hKpApSIWgMSuchy7GMVxFKdAb09QW2Yzo3kfzTyEroBMAIicLuZPdy8TSgAmgkhgmTxCF8AoYwwoFcdoCJznmAngJ2gss_yAAZz2GJEMizx7H6BxjJ-kLyFkmtJzNKCUcp6RdIjquW-qsHX1OumMb0KrqsTVNrRedS7UST8l2lRVEs3am7rbbTfxT-DVD7ZV-J56V2O96Xph0nyoaLAOddeq2CVfrjQh8U63IerQbC_RmVVVNON9H6G3-_nr7BEvnx8Ws9sldikhHc4gNVaBotxmTJa60GCU5IUQeX-21VLaPKWageyDkLJUnJQFCE50KSQRNh2hm51vsym8KVdN67xqt6vD4z3hekdwxph_eB9z-gsXLGwI</recordid><startdate>20110101</startdate><enddate>20110101</enddate><creator>Massoudi, A.</creator><creator>Sowmya, A.</creator><creator>Mele, K.</creator><creator>Semenovich, D.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope></search><sort><creationdate>20110101</creationdate><title>Employing temporal information for cell segmentation using max-flow/min-cut in phase-contrast video microscopy</title><author>Massoudi, A. ; Sowmya, A. ; Mele, K. ; Semenovich, D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i300t-713efa1a25f749dcbc1ea95b668570fc99f832c41912299da50db1650cd6906f3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithms</topic><topic>Biomedical imaging</topic><topic>Cell Tracking - methods</topic><topic>Image edge detection</topic><topic>Image Enhancement - methods</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Image segmentation</topic><topic>Microscopy</topic><topic>Microscopy, Phase-Contrast - methods</topic><topic>Microscopy, Video - methods</topic><topic>Models, Biological</topic><topic>Object segmentation</topic><topic>Pattern Recognition, Automated - methods</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Shape</topic><topic>Subtraction Technique</topic><toplevel>online_resources</toplevel><creatorcontrib>Massoudi, A.</creatorcontrib><creatorcontrib>Sowmya, A.</creatorcontrib><creatorcontrib>Mele, K.</creatorcontrib><creatorcontrib>Semenovich, D.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Massoudi, A.</au><au>Sowmya, A.</au><au>Mele, K.</au><au>Semenovich, D.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Employing temporal information for cell segmentation using max-flow/min-cut in phase-contrast video microscopy</atitle><btitle>2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society</btitle><stitle>IEMBS</stitle><addtitle>Conf Proc IEEE Eng Med Biol Soc</addtitle><date>2011-01-01</date><risdate>2011</risdate><volume>2011</volume><spage>5985</spage><epage>5988</epage><pages>5985-5988</pages><issn>1094-687X</issn><issn>1557-170X</issn><eissn>1558-4615</eissn><isbn>9781424441211</isbn><isbn>1424441218</isbn><eisbn>1424441226</eisbn><eisbn>1457715899</eisbn><eisbn>9781457715891</eisbn><eisbn>9781424441228</eisbn><abstract>Cell segmentation is a crucial step in many biomedical image analysis applications and it can be considered as an important part of a tracking system. Segmentation in phase-contrast images is a challenging task since in this imaging technique, the background intensity is approximately similar to the cell pixel intensity. In this paper we propose an interactive automatic pixel level segmentation algorithm, that uses temporal information to improve the segmentation result. This algorithm is based on the max-flow/min-cut algorithm and can be solved in polynomial time. This method is not restricted to any specific cell shape and segments cells of various shapes and sizes. The results of the proposed algorithm show that using the temporal information does improve segmentation considerably.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>22255703</pmid><doi>10.1109/IEMBS.2011.6091479</doi><tpages>4</tpages></addata></record> |
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| identifier | ISSN: 1094-687X |
| ispartof | 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011, Vol.2011, p.5985-5988 |
| issn | 1094-687X 1557-170X 1558-4615 |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Algorithms Biomedical imaging Cell Tracking - methods Image edge detection Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image segmentation Microscopy Microscopy, Phase-Contrast - methods Microscopy, Video - methods Models, Biological Object segmentation Pattern Recognition, Automated - methods Reproducibility of Results Sensitivity and Specificity Shape Subtraction Technique |
| title | Employing temporal information for cell segmentation using max-flow/min-cut in phase-contrast video microscopy |
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