Longitudinal three-label segmentation of knee cartilage

Published

Journal Article

Automatic accurate segmentation methods are needed to assess longitudinal cartilage changes in osteoarthritis (OA). We propose a novel general spatio-temporal three-label segmentation method to encourage segmentation consistency across time in longitudinal image data. The segmentation is formulated as a convex optimization problem which allows for the computation of globally optimal solutions. The longitudinal segmentation is applied within an automatic knee cartilage segmentation pipeline. Experimental results demonstrate that the longitudinal segmentation improves the segmentation consistency in comparison to the temporally-independent segmentation. © 2013 IEEE.

Full Text

Duke Authors

Cited Authors

  • Shan, L; Charles, C; Niethammer, M

Published Date

  • August 22, 2013

Published In

Start / End Page

  • 1376 - 1379

Electronic International Standard Serial Number (EISSN)

  • 1945-8452

International Standard Serial Number (ISSN)

  • 1945-7928

Digital Object Identifier (DOI)

  • 10.1109/ISBI.2013.6556789

Citation Source

  • Scopus