The existence of short T2 tissues and high ordered collagen fibers in cartilage render it “invisible” to conventional MR and sensitive to the magic angle effect. Segmentation is the first step to obtain parameters of cartilage, which is often performed manually (time-consuming and variable). Automatic segmentation and providing a biomarker that visualizes both short and long T2 tissues and insensitive to the magic angle effect is desideratum. U-Net is based on CNN to process images. The purpose of this study is to describe and evaluate the pipeline of fully-automatic segmentation of cartilage and extraction of MMF in 3D UTE-Cones-MT modeling.