Dynamic Fisher-Tippett Region Merging Approach to Transrectal Ultrasound Prostate Lesion Segmentation

In this paper, a computerized approach to segmenting prostate lesions in transrectal ultrasound (TRUS) images is presented. The segmentation of prostate lesions from TRUS images is very challenging due to issues such as poor contrast, low signal-to-noise ratios, and irregular shape variations. To address these issues, a novel approach is employed to segment the lesions from the surrounding prostate, where region merging is performed via a region merging likelihood function based on regional statistics as well as Fisher-Tippett statistics. Experimental results using TRUS prostate images demonstrate that the proposed Fisher-Tippett region merging (FTRM) approach achieves more accurate segmentation of prostate lesions when compared to other segmentation methods.