Towards Shape-based Knee Osteoarthritis Classification using Graph Convolutional Networks

  • 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.
Metadaten
Author:Christoph von TycowiczORCiD
Document Type:In Proceedings
Parent Title (English):2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020)
Year of first publication:2020
ArXiv Id:http://arxiv.org/abs/1910.06119
DOI:https://doi.org/10.1109/ISBI45749.2020.9098687