Title:
A shape-based approach to the segmentation of medical imagery using level sets
A shape-based approach to the segmentation of medical imagery using level sets
| dc.contributor.author | Tsai, Andy | en_US |
| dc.contributor.author | Yezzi, Anthony | en_US |
| dc.contributor.author | Wells, William, III | en_US |
| dc.contributor.author | Tempany, Clare | en_US |
| dc.contributor.author | Tucker, Dewey | en_US |
| dc.contributor.author | Fan, Ayres | en_US |
| dc.contributor.author | Grimson, W. Eric | en_US |
| dc.contributor.author | Willsky, Alan S. | en_US |
| dc.contributor.corporatename | Georgia Institute of Technology. School of Electrical and Computer Engineering | en_US |
| dc.contributor.corporatename | Brigham and Women’s Hospital | en_US |
| dc.contributor.corporatename | Harvard Medical School | en_US |
| dc.contributor.corporatename | Massachusetts Institute of Technology. Artificial Intelligence Laboratory | en_US |
| dc.contributor.corporatename | Massachusetts Institute of Technology. Laboratory for Information and Decision Systems | en_US |
| dc.date.accessioned | 2013-09-09T19:43:41Z | |
| dc.date.available | 2013-09-09T19:43:41Z | |
| dc.date.issued | 2003-02 | |
| dc.description | ©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | en_US |
| dc.description | DOI: 10.1109/TMI.2002.808355 | en_US |
| dc.description.abstract | We propose a shape-based approach to curve evolution for the segmentation of medical images containing known object types. In particular, motivated by the work of Leventon, Grimson, and Faugeras (2000), we derive a parametric model for an implicit representation of the segmenting curve by applying principal component analysis to a collection of signed distance representations of the training data. The parameters of this representation are then manipulated to minimize an objective function for segmentation. The resulting algorithm is able to handle multidimensional data, can deal with topological changes of the curve, is robust to noise and initial contour placements, and is computationally efficient. At the same time, it avoids the need for point correspondences during the training phase of the algorithm. We demonstrate this technique by applying it to two medical applications; two-dimensional segmentation of cardiac magnetic resonance imaging (MRI) and three-dimensional segmentation of prostate MRI. | en_US |
| dc.identifier.citation | Tsai, A.; Yezzi, A., Jr.; Wells, W.; Tempany, C.; Tucker, D.; Fan, A.; Grimson, W.E.; Willsky, A., "A shape-based approach to the segmentation of medical imagery using level sets," IEEE Transactions on Medical Imaging, 22 (2), 137,154 (Feb. 2003) | en_US |
| dc.identifier.doi | 10.1109/TMI.2002.808355 | |
| dc.identifier.issn | 0278-0062 | |
| dc.identifier.uri | http://hdl.handle.net/1853/48910 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.publisher.original | Institute of Electrical and Electronics Engineers | en_US |
| dc.subject | Active contours | en_US |
| dc.subject | Binary image alignment | en_US |
| dc.subject | Cardiac MRI segmentation | en_US |
| dc.subject | Curve evolution | en_US |
| dc.subject | Deformable model | en_US |
| dc.subject | Distance transforms | en_US |
| dc.subject | Eigenshapes | en_US |
| dc.subject | Implicit shape representation | en_US |
| dc.subject | Medical image segmentation | en_US |
| dc.subject | Parametric shape model | en_US |
| dc.subject | Principal component analysis | en_US |
| dc.subject | Prostate segmentation | en_US |
| dc.subject | Shape prior | en_US |
| dc.subject | Statistical shape model | en_US |
| dc.title | A shape-based approach to the segmentation of medical imagery using level sets | en_US |
| dc.type | Text | |
| dc.type.genre | Article | |
| dspace.entity.type | Publication | |
| local.contributor.author | Yezzi, Anthony | |
| local.contributor.corporatename | School of Electrical and Computer Engineering | |
| local.contributor.corporatename | College of Engineering | |
| relation.isAuthorOfPublication | 53ee63a2-04fd-454f-b094-02a4601962d8 | |
| relation.isOrgUnitOfPublication | 5b7adef2-447c-4270-b9fc-846bd76f80f2 | |
| relation.isOrgUnitOfPublication | 7c022d60-21d5-497c-b552-95e489a06569 |
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