Fully automated detection of prostate transition zone tumors on T2‐weighted and apparent diffusion coefficient (ADC) map MR images using U‐Net ensemble

Purpose Accurate detection of transition zone (TZ) prostate cancer (PCa) on magnetic resonance imaging (MRI) remains challenging using clinical subjective assessment due to overlap between PCa and benign prostatic hyperplasia (BPH). The objective of this paper is to describe a deep‐learning‐based framework for fully automated detection of PCa in the TZ using T2‐weighted (T2W) and apparent diffusion coefficient (ADC) map MR images. Method This...