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Content Provider | IEEE Xplore Digital Library |
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Author | Pardo, X.M. Radeva, P. |
Copyright Year | 2000 |
Description | Author affiliation: Dept. Electron. e Comput., Santiago de Compostela Univ., Spain (Pardo, X.M.) |
Abstract | We propose a new statistic deformable model that we call discriminant snake for 3D reconstruction in volumetric images. Our discriminant snake generalises the classical snake attracted by edge points; it deforms due to a generalised contour representation. The snake selects and classifies image features by a parametric classifier and each snaxel deforms to minimise the dissimilarity between the learned and found image features inside the feature space. We apply our statistic snake to segment anatomical organs and the results are very encouraging. |
Starting Page | 336 |
Ending Page | 339 |
File Size | 426253 |
Page Count | 4 |
File Format | |
ISBN | 0769507506 |
ISSN | 10514651 |
DOI | 10.1109/ICPR.2000.902927 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2000-09-03 |
Publisher Place | Spain |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Image reconstruction Biomedical imaging Shape Parametric statistics Deformable models Image segmentation Supervised learning Image edge detection Image sequences Statistical analysis |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition |
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