Detection and local Staging of Prostate Cancer Using Machine Learning Algorithm

Abstract

Prostate Cancer (PCa) occurs in the prostate that generates the seminal fluid for men. PCa is the second commonly detected ailment of men all over the world and composes of twenty eight percent of cancers in men. Hence its identification is crucial focus in cancer research. PCa symptoms are with troubled urination, identified through blood semen, bone pain. The diagnosis of prostate-specific antigen (PSA) and the use of pathological and demographic factors such as Gleason score, clinical stage, age, etc. remain the current standard in the planning and decision-making of PCa treatment. The improper symptoms of PCa are a challenge to identify at an early stage. Segmentation of Prostate and its classification is a challenging process, and the technical hitches basically vary with one medical imaging methodology on to the others. The deep learning (DL) algorithms, especially CNNs have become possible technique for segmentation and classification within image analysis. newline