AUTOMATIC MULTI-ATLAS-BASED CARTILAGE SEGMENTATION FROM KNEE MR IMAGES.
Proc IEEE Int Symp Biomed Imaging
; 2012: 1028-1031, 2012 Dec 31.
Article
em En
| MEDLINE
| ID: mdl-24443678
ABSTRACT
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).
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2012
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Article