Automatic atlas-based three-label cartilage segmentation from MR knee images
Published
Journal Article
This paper proposes a method to build a bone-cartilage atlas of the knee and to use it to automatically segment femoral and tibial cartilage from T1 weighted magnetic resonance (MR) images. Anisotropic spatial regularization is incorporated into a three-label segmentation framework to improve segmentation results for the thin cartilage layers. We jointly use the atlas information and the output of a probabilistic k nearest neighbor classifier within the segmentation method. The resulting cartilage segmentation method is fully automatic. Validation results on 18 knee MR images against manual expert segmentations from a dataset acquired for osteoarthritis research show good performance for the segmentation of femoral and tibial cartilage (mean Dice similarity coefficient of 78.2% and 82.6% respectively). © 2012 IEEE.
Full Text
Duke Authors
Cited Authors
- Shan, L; Charles, C; Niethammer, M
Published Date
- April 24, 2012
Published In
- Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis
Start / End Page
- 241 - 246
Digital Object Identifier (DOI)
- 10.1109/MMBIA.2012.6164757
Citation Source
- Scopus