Gland and Zonal Segmentation of Prostate on T2W MR Images.

For many years, prostate segmentation on MR images concerned only the extraction of the entire gland. Currently, in the focal treatment era, there is a continuously increasing need for the separation of the different parts of the organ. In this paper, we propose an automatic segmentation method based on the use of T2W images and atlas images to segment the prostate and to isolate the peripheral and transition zones. The algorithm consists of two stages. First, the target image is registered with each zonal atlas image then the segmentation is obtained by the application of an evidential C-Means clustering. The method was evaluated on a representative and multi-centric image base and yielded mean Dice accuracy values of 0.81, 0.70, and 0.62 for the prostate, the transition zone, and peripheral zone, respectively.

A survey of prostate modeling for image analysis.

Computer technology is widely used for multimodal image analysis of the prostate gland. Several techniques have been developed, most of which incorporate a priori knowledge extracted from organ features. Knowledge extraction and modeling are multi-step tasks. Here, we review these steps and classify the modeling according to the data analysis methods employed and the features used. We conclude with a survey of some clinical applications where these techniques are employed.