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Automatic vessel tracking and segmentation using epicardial ultrasound in bypass surgery
Epicardial ultrasound has been suggested as an alternative approach for assessing the quality of coronary artery bypass graft anastomoses. Using automatic tracking and segmentation of the anastomotic vessel lumen in transverse epicardial ultrasound images it is possible to quantitatively assess the...
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| creator | Jorgensen, A. S. Schmidt, S. E. Staalsen, Niels-Henrik Ostergaard, L. R. |
| description | Epicardial ultrasound has been suggested as an alternative approach for assessing the quality of coronary artery bypass graft anastomoses. Using automatic tracking and segmentation of the anastomotic vessel lumen in transverse epicardial ultrasound images it is possible to quantitatively assess the stenosis degree of surgical errors. We propose an automatic vessel tracking and segmentation framework that can detect, track, and segment vessels through ultrasound sequences with the purpose of enabling stenosis quantification. An average accuracy of 92.86% in detecting vessels was obtained 78.51% of the vessel segmentations were assessed as correct. |
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S. ; Schmidt, S. E. ; Staalsen, Niels-Henrik ; Ostergaard, L. R.</creator><creatorcontrib>Jorgensen, A. S. ; Schmidt, S. E. ; Staalsen, Niels-Henrik ; Ostergaard, L. R.</creatorcontrib><description>Epicardial ultrasound has been suggested as an alternative approach for assessing the quality of coronary artery bypass graft anastomoses. Using automatic tracking and segmentation of the anastomotic vessel lumen in transverse epicardial ultrasound images it is possible to quantitatively assess the stenosis degree of surgical errors. We propose an automatic vessel tracking and segmentation framework that can detect, track, and segment vessels through ultrasound sequences with the purpose of enabling stenosis quantification. 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An average accuracy of 92.86% in detecting vessels was obtained 78.51% of the vessel segmentations were assessed as correct.</description><subject>Arteries</subject><subject>Image segmentation</subject><subject>Motion segmentation</subject><subject>Quality control</subject><subject>Surgery</subject><subject>Tracking</subject><subject>Ultrasonic imaging</subject><issn>0276-6574</issn><issn>2325-8853</issn><isbn>1467320765</isbn><isbn>9781467320764</isbn><isbn>9781467320757</isbn><isbn>9781467320771</isbn><isbn>1467320757</isbn><isbn>1467320773</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1jMlqwzAURdUJ6qT5gm70AwZZT-MyhE4Q6KaF7oIkPxu1nrDsgv--Lm1WF8453Auys9oUQmngTEt9STIOXObGSLgim7NQ8ppkjGuVK6nFLdmk9MlYYa2WGfnYz1PfuikG-o0pYUOn0YWv2NXUdSVNWLfYTavvOzqnX4xDDG4so2vo3Kxx6uc1jB31y-BSomkeaxyXO3JTuSbh7n-35P3x4e3wnB9fn14O-2MeCy2nXDgLwAz3Thh0vsLKV55JCeBZJZUIHFTBSmUlhlJ44Gh48CHIgpe2rDxsyf3fb0TE0zDG1o3LSQnOoNDwA_KbUxM</recordid><startdate>201209</startdate><enddate>201209</enddate><creator>Jorgensen, A. 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R.</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/IET Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Jorgensen, A. S.</au><au>Schmidt, S. E.</au><au>Staalsen, Niels-Henrik</au><au>Ostergaard, L. R.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Automatic vessel tracking and segmentation using epicardial ultrasound in bypass surgery</atitle><btitle>2012 Computing in Cardiology</btitle><stitle>CiC</stitle><date>2012-09</date><risdate>2012</risdate><spage>9</spage><epage>12</epage><pages>9-12</pages><issn>0276-6574</issn><eissn>2325-8853</eissn><isbn>1467320765</isbn><isbn>9781467320764</isbn><eisbn>9781467320757</eisbn><eisbn>9781467320771</eisbn><eisbn>1467320757</eisbn><eisbn>1467320773</eisbn><abstract>Epicardial ultrasound has been suggested as an alternative approach for assessing the quality of coronary artery bypass graft anastomoses. Using automatic tracking and segmentation of the anastomotic vessel lumen in transverse epicardial ultrasound images it is possible to quantitatively assess the stenosis degree of surgical errors. We propose an automatic vessel tracking and segmentation framework that can detect, track, and segment vessels through ultrasound sequences with the purpose of enabling stenosis quantification. An average accuracy of 92.86% in detecting vessels was obtained 78.51% of the vessel segmentations were assessed as correct.</abstract><pub>IEEE</pub><tpages>4</tpages></addata></record> |
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| identifier | ISSN: 0276-6574 |
| ispartof | 2012 Computing in Cardiology, 2012, p.9-12 |
| issn | 0276-6574 2325-8853 |
| language | eng |
| recordid | cdi_ieee_primary_6420317 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Arteries Image segmentation Motion segmentation Quality control Surgery Tracking Ultrasonic imaging |
| title | Automatic vessel tracking and segmentation using epicardial ultrasound in bypass surgery |
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