Monte Carlo despeckling of transrectal ultrasound images of the prostate

In this paper, a novel stochastic method is developed for despeckling transrectal ultrasound (TRUS) images of the prostate. By incorporating the circular probe acquisition particularities and speckle noise statistics of TRUS images of the prostate into a likelihood-weighted Monte Carlo estimation scheme, the proposed method can better remove speckle noise while preserving image structures and details that are relevant for image screening, allowing for a better delineation of the lesion contour. Our in-silico and in-vivo experimental results are promising, which was confirmed by a clinical evaluation of the in-vivo test cases by experienced clinicians, and indicate that our method potentially can perform better than other previously proposed methods.