Background:
Prostate cancer is the second most common cancer-related cause of death in men. Accurate diagnosis of prostate cancer plays an important role in decreasing mortality rates. European Association of Urology (EAU) suggests multiparametric MRI (mp-MRI) of the prostate as a noninvasive method to evaluate prostate lesions. To leverage the interbreeder variability in the interpretation of mp-MRI, computer-aided diagnostic (CAD) systems can be used for automatic detection and characterization of prostate lesions.