Title:
Hybrid geodesic region-based curve evolutions for image segmentation
Hybrid geodesic region-based curve evolutions for image segmentation
| dc.contributor.author | Lankton, Shawn | |
| dc.contributor.author | Nain, Delphine | |
| dc.contributor.author | Yezzi, Anthony | |
| dc.contributor.author | Tannenbaum, Allen R. | |
| dc.contributor.corporatename | Georgia Institute of Technology. College of Computing | |
| dc.contributor.corporatename | Georgia Institute of Technology. School of Electrical and Computer Engineering | |
| dc.date.accessioned | 2009-06-24T19:08:37Z | |
| dc.date.available | 2009-06-24T19:08:37Z | |
| dc.date.issued | 2007-02-18 | |
| dc.description | ©2007 SPIE--The International Society for Optical Engineering. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. The electronic version of this article is the complete one and can be found online at: http://dx.doi.org/10.1117/12.709700 | en |
| dc.description | Medical imaging 2007: Physics of medical imaging, 18-22 February 2007, San Diego, California, USA. | |
| dc.description | DOI:10.1117/12.709700 | |
| dc.description.abstract | In this paper we present a gradient descent flow based on a novel energy functional that is capable of producing robust and accurate segmentations of medical images. This flow is a hybridization of local geodesic active contours and more global region-based active contours. The combination of these two methods allows curves deforming under this energy to find only significant local minima and delineate object borders despite noise, poor edge information, and heterogeneous intensity profiles. To accomplish this, we construct a cost function that is evaluated along the evolving curve. In this cost, the value at each point on the curve is based on the analysis of interior and exterior means in a local neighborhood around that point. We also demonstrate a novel mathematical derivation used to implement this and other similar flows. Results for this algorithm are compared to standard techniques using medical and synthetic images to demonstrate the proposed method's robustness and accuracy as compared to both edge-based and region-based alone. | en |
| dc.identifier.citation | Shawn Lankton, Delphine Nain, Anthony Yezzi, and Allen Tannenbaum, "Hybrid geodesic region-based curve evolutions for image segmentation," Medical Imaging 2007: Physics of Medical Imaging, Jiang Hsieh, Michael J. Flynn, Editors, Proc. of SPIE Vol. 6510, 65104U, (2007) | en |
| dc.identifier.issn | 0277-786X | |
| dc.identifier.uri | http://hdl.handle.net/1853/28604 | |
| dc.language.iso | en_US | en |
| dc.publisher | Georgia Institute of Technology | en |
| dc.publisher.original | Society of Photo-Optical Instrumentation Engineers | |
| dc.subject | Algorithms | en |
| dc.title | Hybrid geodesic region-based curve evolutions for image segmentation | en |
| dc.type | Text | |
| dc.type.genre | Proceedings | |
| dspace.entity.type | Publication | |
| local.contributor.author | Yezzi, Anthony | |
| local.contributor.corporatename | Wallace H. Coulter Department of Biomedical Engineering | |
| relation.isAuthorOfPublication | 53ee63a2-04fd-454f-b094-02a4601962d8 | |
| relation.isOrgUnitOfPublication | da59be3c-3d0a-41da-91b9-ebe2ecc83b66 |