Automatic Multi-Atlas-Based Cartilage Segmentation from Knee MR Images

TitleAutomatic Multi-Atlas-Based Cartilage Segmentation from Knee MR Images
Publication TypeConference Paper
Year of Publication2012
AuthorsShan L, Charles C, Niethammer M
Conference NameProceedings of the International Symposium on Biomedical Imaging (ISBI)

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).