Prostate Cancer Classification and Interpretation With Multiparametric Magnetic Resonance Imaging and Gleason Grade Score Using DarkNet53 Model.

Background: Prostate Cancer (PCa) increases the mortality rate of males worldwide and is caused by genetics, lifestyle, and age reasons. The existing automated PCa classification systems face difficulties with overfitting issues, and non-generalizability, leading to poor classification performance.

Objective: On this account, this study proposes an automated classification of PCa from MRI images using a hybrid weighted mean of vectors-optimized DarkNet53 classifier model.