[Segmentation of the prostate on magnetic resonance images using an ellipsoidal shape prior constraint algorithm]

We propose a novel strategy for multi-atlas-based image segmentation of the prostate on magnetic resonance (MR) images using an ellipsoidal shape prior constraint algorithm. An ellipsoidal shape prior constraint was incorporated into the process of multi-atlas based segmentation to restrict the regions of interest on the prostate images and avoid the interference by the surrounding tissues and organs in atlas selection. In the subsequent process of atlas fusion, the ellipsoidal shape prior constraint calibrated and compensated for the shape prior obtained by the registration technique to avoid incorrect segmentation caused by registration errors. Evaluation of this proposed method on prostate images from 50 subjects showed that this algorithm was effective and yielded a mean Dice similarity coefficients of 0.8812, suggesting its high accuracy and robustness to segment the prostate on MR images.