Co-dimension 2 Geodesic Active Contours for MRA Segmentation
Automatic and semi-automatic magnetic resonance angiography (MRA)s segmentation techniques can potentially save radiologists larges amounts of time required for manual segmentation and cans facilitate further data analysis. The proposed MRAs segmentation method uses a mathematical modeling technique...
| Main Authors: | , , , , , |
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| Language: | en_US |
| Published: |
2004
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/5928 |
| _version_ | 1826192988682846208 |
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| author | Lorigo, Liana M. Faugeras, Olivier Grimson, W.E.L. Keriven, Renaud Kikinis, Ron Westin, Carl-Fredrik |
| author_facet | Lorigo, Liana M. Faugeras, Olivier Grimson, W.E.L. Keriven, Renaud Kikinis, Ron Westin, Carl-Fredrik |
| author_sort | Lorigo, Liana M. |
| collection | MIT |
| description | Automatic and semi-automatic magnetic resonance angiography (MRA)s segmentation techniques can potentially save radiologists larges amounts of time required for manual segmentation and cans facilitate further data analysis. The proposed MRAs segmentation method uses a mathematical modeling technique whichs is well-suited to the complicated curve-like structure of bloods vessels. We define the segmentation task as ans energy minimization over all 3D curves and use a level set methods to search for a solution. Ours approach is an extension of previous level set segmentations techniques to higher co-dimension. |
| first_indexed | 2024-09-23T09:31:55Z |
| id | mit-1721.1/5928 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T09:31:55Z |
| publishDate | 2004 |
| record_format | dspace |
| spelling | mit-1721.1/59282019-04-12T08:28:13Z Co-dimension 2 Geodesic Active Contours for MRA Segmentation Lorigo, Liana M. Faugeras, Olivier Grimson, W.E.L. Keriven, Renaud Kikinis, Ron Westin, Carl-Fredrik medical image analysis segmentation smagnetic resonance angiography active contours slevel sets Automatic and semi-automatic magnetic resonance angiography (MRA)s segmentation techniques can potentially save radiologists larges amounts of time required for manual segmentation and cans facilitate further data analysis. The proposed MRAs segmentation method uses a mathematical modeling technique whichs is well-suited to the complicated curve-like structure of bloods vessels. We define the segmentation task as ans energy minimization over all 3D curves and use a level set methods to search for a solution. Ours approach is an extension of previous level set segmentations techniques to higher co-dimension. 2004-10-04T14:15:21Z 2004-10-04T14:15:21Z 1999-08-11 AIM-1662 http://hdl.handle.net/1721.1/5928 en_US AIM-1662 14 p. 6965388 bytes 918981 bytes application/postscript application/pdf application/postscript application/pdf |
| spellingShingle | medical image analysis segmentation smagnetic resonance angiography active contours slevel sets Lorigo, Liana M. Faugeras, Olivier Grimson, W.E.L. Keriven, Renaud Kikinis, Ron Westin, Carl-Fredrik Co-dimension 2 Geodesic Active Contours for MRA Segmentation |
| title | Co-dimension 2 Geodesic Active Contours for MRA Segmentation |
| title_full | Co-dimension 2 Geodesic Active Contours for MRA Segmentation |
| title_fullStr | Co-dimension 2 Geodesic Active Contours for MRA Segmentation |
| title_full_unstemmed | Co-dimension 2 Geodesic Active Contours for MRA Segmentation |
| title_short | Co-dimension 2 Geodesic Active Contours for MRA Segmentation |
| title_sort | co dimension 2 geodesic active contours for mra segmentation |
| topic | medical image analysis segmentation smagnetic resonance angiography active contours slevel sets |
| url | http://hdl.handle.net/1721.1/5928 |
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