TY - JFULL AU - Ali Rafiee and Ahad Salimi and Ali Reza Roosta PY - 2008/10/ TI - A Novel Prostate Segmentation Algorithm in TRUS Images T2 - International Journal of Medical and Health Sciences SP - 317 EP - 322 VL - 2 SN - 1307-6892 UR - https://publications.waset.org/pdf/201 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 21, 2008 N2 - Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease accurate detection of prostate boundaries in transrectal ultrasound (TRUS) images is required. This is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a novel method for automatic prostate segmentation in TRUS images is presented. This method involves preprocessing (edge preserving noise reduction and smoothing) and prostate segmentation. The speckle reduction has been achieved by using stick filter and top-hat transform has been implemented for smoothing. A feed forward neural network and local binary pattern together have been use to find a point inside prostate object. Finally the boundary of prostate is extracted by the inside point and an active contour algorithm. A numbers of experiments are conducted to validate this method and results showed that this new algorithm extracted the prostate boundary with MSE less than 4.6% relative to boundary provided manually by physicians. ER -