Automatic multi-atlas-based cartilage segmentation from knee MR images
Published
Journal Article
In this paper, we propose a multi-atlas-based method to automatically segment the femoral and tibial cartilage from T1 weighted magnetic resonance (MR) knee images. The segmentation result is a joint decision of the spatial priors from a multi-atlas registration and the local likelihoods within a Bayesian framework. The cartilage likelihoods are obtained from a probabilistic k nearest neighbor classification. Validation results on 18 knee MR images against the 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 75.2% and 81.7% respectively). © 2012 IEEE.
Full Text
Duke Authors
Cited Authors
- Shan, L; Charles, C; Niethammer, M
Published Date
- August 15, 2012
Published In
Start / End Page
- 1028 - 1031
Electronic International Standard Serial Number (EISSN)
- 1945-8452
International Standard Serial Number (ISSN)
- 1945-7928
Digital Object Identifier (DOI)
- 10.1109/ISBI.2012.6235733
Citation Source
- Scopus