Use of 2D U-Net Convolutional Neural Networks for Automated Cartilage and Meniscus Segmentation of Knee MR Imaging Data to Determine Relaxometry and Morphometry

Berk Norman, Valentina Pedoia, Sharmila Majumdar

Abstract: We aim to analyze how automatic segmentation performances translate in accuracy and precision to morphology and relaxometry in osteoarthritis compared with manual segmentations and increase the speed and accuracy of the work flow that uses quantitative MR imaging to study knee degenerative diseases.