A Deep Learning-Based Tool for Analyzing the Female Reproductive System in MR images

MRI is a powerful imaging technique for examining the anatomy of the female reproductive system. However, due to cost-related concerns, ease of access, acquisition time, and necessity of expert reviewers for MR images, ultrasound is the primary modality of choice. To mitigate some of these concerns, we developed an AI-driven tool comprising seven neural networks that segments the regions of interest for the whole uterus, uterine zones, ovaries, and further identifies common benign gynecological conditions. We evaluated our package on a large representative population of 2955 sagittal T2-weighted pelvic scans to obtain normative aging-curves for various regions of interest.