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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Roula, M.A. Bouridane, A. Kurugollu, F. |
| Copyright Year | 2004 |
| Description | Author affiliation: Sch. of Comput. Sci., Queen's Univ., Belfast, UK (Roula, M.A.; Bouridane, A.; Kurugollu, F.) |
| Abstract | This paper addresses the problem of automatic segmentation of nuclei in histopathological images. A novel method, inspired from active contour models is proposed. An evolutionary based approach, which guarantees convergence to global minimum energies has been used to solve the combinatorial optimization problem of snakes. The computational complexity, often associated with evolutionary approaches, has been reduced by short cutting the natural evolution step by means of replacing standard mutation with an oriented stochastic mutation process. Results have shown the efficiency of this method both in terms of accuracy and fast computation. |
| Starting Page | 127 |
| Ending Page | 130 |
| File Size | 284018 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780385543 |
| ISSN | 15224880 |
| DOI | 10.1109/ICIP.2004.1418706 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-10-24 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image segmentation Convergence Cancer Active contours Genetic mutations Pathology Shape Dynamic programming Computer science Stochastic processes |
| Content Type | Text |
| Resource Type | Article |
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