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Leveraging Foundation Models for Content-Based Medical Image Retrieval in Radiology
March 12, 2024, 4:48 a.m. | Stefan Denner, David Zimmerer, Dimitrios Bounias, Markus Bujotzek, Shuhan Xiao, Lisa Kausch, Philipp Schader, Tobias Penzkofer, Paul F. J\"ager, Klaus
cs.CV updates on arXiv.org arxiv.org
Abstract: Content-based image retrieval (CBIR) has the potential to significantly improve diagnostic aid and medical research in radiology. Current CBIR systems face limitations due to their specialization to certain pathologies, limiting their utility. In response, we propose using vision foundation models as powerful and versatile off-the-shelf feature extractors for content-based medical image retrieval. By benchmarking these models on a comprehensive dataset of 1.6 million 2D radiological images spanning four modalities and 161 pathologies, we identify weakly-supervised …
abstract arxiv cs.cv cs.ir current diagnostic face foundation image limitations medical medical research radiology research retrieval systems type utility vision
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