Towards Shape-based Knee Osteoarthritis Classification using Graph Convolutional Networks
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Oct 2019.
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2 papers.