Segmentation and Classification of Prostate Gland Using TRUS Images

Any detection on its early stage proves to provide a high degree of survival for a person and for this diagnosis plays a major role.The diagnosis in a nutshell should be accurate and absolute with due importance given, even to the minutest detail . From of old, the speckles have been viewed as an obstacle in the process of diagnosis. But here comes a proposal to turn them into success. Here the size and orientation of the speckles are observed to explore their intrinsic properties .The accurate segmentation is carried out by Transrectal ultrasound(TRUS) image based diagnosis for the detection of prostate cancer. The TRUS images are cut into arc like strips to obtain the different speckle sizes. Then the individual feature vector is induced to obtain the residuals.The residuals along with the inherited spatial coherence from the biological tissue forms the segment with the application of neural networks. Later the fine -tuned segments are integrated with prior shape, dark to light intensity ratio near the boundaries and the like.