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