On the use of coupled shape priors for segmentation of magnetic resonance images of the knee.

ABSTRACT: Active contour techniques have been widely employed for medical image segmentation. Significant effort has been focused on the use of training data to build prior statistical models applicable specifically to problems where the objects of interest are embedded in cluttered background. Usually, the training data consist of whole shapes of certain organs or structures obtained manually by clinical experts. The resulting prior models enforce segmentation accuracy uniformly over the entire structure or structures to be identified. In this paper, we consider a new coupled prior shape model which is demonstrated to provide high accuracy, specifically in the region of the interest where precision is most needed for the application of the segmentation of the femur and tibia in magnetic resonance (

SUBMITTER: Pang J 

PROVIDER: S-EPMC4439111 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature