Region and Shape Prior Based Geodesic Active Contour and Application in Cardiac Valve Segmentation
Geodesic active contour is a useful image segmentation method. But it may fail to segment objects disturbed by complex noises. Prior knowledge on certain object is a powerful guidance in image segmentation. We represent region and shape prior of certain object in a form of speed field and incorporat...
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| creator | Shang, Yanfeng Yang, Xin Zhu, Ming Jin, Biao Liu, Ming |
| description | Geodesic active contour is a useful image segmentation method. But it may fail to segment objects disturbed by complex noises. Prior knowledge on certain object is a powerful guidance in image segmentation. We represent region and shape prior of certain object in a form of speed field and incorporate it into Geodesic Active Contours. Region prior constrains the zero level set evolving in certain region and shape prior pulls the curve to the ideal contour. Applications in a large quantity of cardiac valve echocardiographic sequences have shown that the algorithm is a more accurate and efficient image segmentation method. |
| doi_str_mv | 10.1007/11424925_115 |
| format | Conference Proceeding |
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But it may fail to segment objects disturbed by complex noises. Prior knowledge on certain object is a powerful guidance in image segmentation. We represent region and shape prior of certain object in a form of speed field and incorporate it into Geodesic Active Contours. Region prior constrains the zero level set evolving in certain region and shape prior pulls the curve to the ideal contour. Applications in a large quantity of cardiac valve echocardiographic sequences have shown that the algorithm is a more accurate and efficient image segmentation method.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 3540258639</identifier><identifier>ISBN: 9783540258636</identifier><identifier>ISBN: 9783540258605</identifier><identifier>ISBN: 3540258604</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 3540323090</identifier><identifier>EISBN: 9783540323099</identifier><identifier>DOI: 10.1007/11424925_115</identifier><language>eng</language><publisher>Berlin, Heidelberg: Springer Berlin Heidelberg</publisher><subject>Applied sciences ; Artificial intelligence ; Computer science; control theory; systems ; Exact sciences and technology ; Pattern recognition. Digital image processing. 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But it may fail to segment objects disturbed by complex noises. Prior knowledge on certain object is a powerful guidance in image segmentation. We represent region and shape prior of certain object in a form of speed field and incorporate it into Geodesic Active Contours. Region prior constrains the zero level set evolving in certain region and shape prior pulls the curve to the ideal contour. Applications in a large quantity of cardiac valve echocardiographic sequences have shown that the algorithm is a more accurate and efficient image segmentation method.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>3540258639</isbn><isbn>9783540258636</isbn><isbn>9783540258605</isbn><isbn>3540258604</isbn><isbn>3540323090</isbn><isbn>9783540323099</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2005</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNpNkD1PwzAURc2XRCnd-AFeWJACtp_jxGOJoCBVAlFgjV5spxhCEtkBiX9P2jJwlzec8-5wCTnj7JIzll1xLoXUIi05T_fICaSSgQCm2T6ZcMV5AiD1wQ6INFegD8mEAROJziQck1mM72wMcJWDnJDqya1911JsLV29Ye_oY_BdoNcYnaUL11kXvaFzM_hvR4uuHbqvsLXnfd94g8Pm27e0wGA9GvqKzSiu3PrTtcOWnpKjGpvoZn93Sl5ub56Lu2T5sLgv5sukF4INSS1TDZhJk0mhrWBCGW4ANEebS-NyVBaUdoZph6bWWaVMpZSVGVOZqFHBlJzvenuMBps6YGt8LPvgPzH8lFxpzRSko3ex8-KI2rULZdV1H7HkrNxMXP6fGH4Bp9VokQ</recordid><startdate>2005</startdate><enddate>2005</enddate><creator>Shang, Yanfeng</creator><creator>Yang, Xin</creator><creator>Zhu, Ming</creator><creator>Jin, Biao</creator><creator>Liu, Ming</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>IQODW</scope></search><sort><creationdate>2005</creationdate><title>Region and Shape Prior Based Geodesic Active Contour and Application in Cardiac Valve Segmentation</title><author>Shang, Yanfeng ; Yang, Xin ; Zhu, Ming ; Jin, Biao ; Liu, Ming</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p220t-f4593a74c7429d2026c1c3391ad84ce8a6d369ec09eacf97b6cb66d470672fa63</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>Exact sciences and technology</topic><topic>Pattern recognition. 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| identifier | ISSN: 0302-9743 |
| ispartof | Computational Science and Its Applications – ICCSA 2005, 2005, p.1102-1110 |
| issn | 0302-9743 1611-3349 |
| language | eng |
| recordid | cdi_pascalfrancis_primary_16990635 |
| source | Springer Books |
| subjects | Applied sciences Artificial intelligence Computer science control theory systems Exact sciences and technology Pattern recognition. Digital image processing. Computational geometry |
| title | Region and Shape Prior Based Geodesic Active Contour and Application in Cardiac Valve Segmentation |
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