D6 - Virtual Bone Shape Aging
Francesco Caliva, Alejandro Morales Martinez, Sharmila Majumdar, Valentina Pedoia
We use deep learning to age knee bone surfaces four years. We propose to encode an MRI-based bone surface in a spherical coordinate format, and use these spherical maps to predict shape changes in a 48 months time frame, in subjects with and without osteoarthritis. The experiments show that a 2D V-Net can predict bone surface shape with a mean absolute error of about 1 mm. Our code is available at https://github.com/fcaliva/Bone_Shape_Virtual_Aging.
Wednesday 7th July
D4-12 (short): Detection and Diagnosis 1 - 16:45 - 17:30 (UTC+2)