Keywords: Prostate, Data Analysis, Artificial Intelligence/ Machine LearningAI-assisted prostate whole-gland and zonal volume quantification enable quantitative reproducibility and enhance read-time efficiency. Our whole-gland AI-segmentation solution enhanced measurement accuracy by 23.59%, compared with traditional volume estimates. Zonal solution enabled us to generate population normative aging-curves and we used a shallow classifier to identify patients with BPH. Our findings show the transitional zone grows 2.05 ml and 3.58 ml per decade for the entire population and patients with BPH, respectively, while peripheral zone grows 0.70 ml per decade. Further, the transitional and peripheral zones grow 2.43 and 1.4 times their size over lifetime.
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