Segmentation of prostate contours for automated diagnosis using ultrasound images: A survey

摘要

Prostate cancer is the most common cancer that affects elderly men. The conventional non-imaging screening test for prostate cancer like prostate antigen (PSA) and digital rectal examination (DRE) tests generally lack specificity. Ultrasound is the most commonly available, inexpensive, non-invasive, and radiation-free imaging modality among all the screening imaging modalities available for prostate cancer diagnosis. The precise segmentation of prostate contours in ultrasound images is crucial in applications such as the exact placement of needles during biopsies, computing the prostate gland volume, and to localize the prostate cancer. Moreover, the low-dose-rate (LDR) brachytherapy treatment in which radioactive seeds are implanted in the prostate region requires accurate contouring of the prostate gland in ultrasound images. Therefore, it is very important to segment the prostrate region accurately for the diagnosis and treatment. This paper aims to present the analysis of existing approaches used for the segmentation of prostate in transrectal ultrasound (TRUS) images. In this survey, different segmentation methods used to extract the prostrate using criteria such as mean absolute distance, Hausdorff distance and time are discussed in detail and compared. (C) 2017 Elsevier B.V. All rights reserved.