English

Towards Shape-based Knee Osteoarthritis Classification using Graph Convolutional Networks

Quantitative Methods 2019-10-15 v1 Image and Video Processing

Abstract

We present a transductive learning approach for morphometric osteophyte grading based on geometric deep learning. We formulate the grading task as semi-supervised node classification problem on a graph embedded in shape space. To account for the high-dimensionality and non-Euclidean structure of shape space we employ a combination of an intrinsic dimension reduction together with a graph convolutional neural network. We demonstrate the performance of our derived classifier in comparisons to an alternative extrinsic approach.

Keywords

Cite

@article{arxiv.1910.06119,
  title  = {Towards Shape-based Knee Osteoarthritis Classification using Graph Convolutional Networks},
  author = {Christoph von Tycowicz},
  journal= {arXiv preprint arXiv:1910.06119},
  year   = {2019}
}
R2 v1 2026-06-23T11:42:57.898Z