Qin, X. and Liu, Y. and Lu, H. and Li, Xuelong and Yan, P. (2012) Coupled directional level set for MR image segmentation. In: UNSPECIFIED (ed.) 11th International Conference on Machine Learning and Applications. Washington, USA: IEEE Computer Society, pp. 185-190. ISBN 9781467346511.
Abstract
Segmenting bladder wall for thickness measuring is a fundamental operation in bladder magnetic resonance (MR) image analysis since thickening of the bladder wall may indicate abnormality. Active contours have been used for bladder wall segmentation, which can be broadly divided into gradient-based and region-based methods, according to the used image features. However, the artifacts in MR images and the complex background outside the bladder lead to significant challenges for segmentation. In this paper, a coupled directional level set model is proposed to segment the outer and inner boundaries simultaneously by exploiting the directional gradient, region information and thickness prior of the bladder wall. With our proposed method, the influence of the artifacts in the bladder lumen and the complicated intensity distribution of soft tissues surrounding the bladder can be appreciably reduced. Promising results on 119 bladder MR images have demonstrated the performance of the presented method.
Metadata
| Item Type: | Book Section |
|---|---|
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Depositing User: | Sarah Hall |
| Date Deposited: | 06 Jun 2013 15:47 |
| Last Modified: | 09 Aug 2023 12:33 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/7329 |
Statistics
Additional statistics are available via IRStats2.
Archive Staff Only (login required)
