Segmentation of Prostate Cancer on TRUS Images Using ML
R. I. Zaev, A. Yu. Romanov, Roman Aleksandrovich Solovyev · 2023
Medical research has made tremendous progress in detecting various pathologies in the human body. There is still the problem of the speed of the process, and the lack of a sufficient number of trained professionals in this field. Detection of prostate cancer, in particular, without surgery is a very labor- intensive process. A neural network-based machine learning algorithm has been proposed to solve this problem, making it possible to see suspected areas of lesions in the organ. In this study, a comprehensive analysis of TRUS image processing approaches was carried out, and an algorithm architecture was developed to segment the affected areas. Based on this analysis, we have developed a system for automatic detection and segmentation of prostate cancer.