Total Knee Replacement prediction using Structural MRIs and 3D Convolutional Neural Networks

Tianyu Wang, Kevin Leung, Kyunghyun Cho, Gregory Chang, Cem M. Deniz

Keywords: MRI, Image Classification, Convolutional Neural Networks, Osteoarthritis, Total Knee Replacement

TL;DR: Using 3D CNN method predict knee OA progression.

Abstract: Osteoarthritis (OA) is a chronic degenerative disorder of joints and is the most common reason leading to total knee joint replacement (TKR). In this work, we developed an automated OA-relevant imaging biomarker identification system based on MR images and deep learning (DL) methods to predict knee OA progression. Our results indicate that the combination of multiple MR images with different contrast and resolution provides the best model to predict TKR with AUC 0.88$\pm$0.02.

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