MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs.

By Pranav Rajpurkar, Jeremy Irvin, Aarti Bagul, Daisy Yi Ding, Tony Duan, Hershel Mehta, Brandon Yang, Kaylie Zhu, Dillon Laird, Robyn L. Ball and 4 more. 2017

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Contrastive Learning of Medical Visual Representations from Paired Images and Text (2020, background): “…(Wang and Wong, 2020), which involves multi-class chest image classiﬁcation into three categories ( COVID19 , non-COVID pneumonia or normal ); and 4) MURA bony abnormality detection (Rajpurkar et al., 2018a), which involves binary classiﬁcation of a musculoskeletal image into abnormal or normal .”
How Artificial Intelligence Is Shaping Medical Imaging Technology: A Survey of Innovations and Applications (2023, background): “[120] MedPix A free online medical image database with over 59,000 indexed and curated images from over 12,000 patients.”
PubMedCLIP: How Much Does CLIP Benefit Visual Question Answering in the Medical Domain? (2023, background): “Previous work (Rajpurkar et al., 2017; Wang et al., 2017; Irvin et al., 2019; Johnson et al., 2019a) also proposes large-scale multi-modal datasets in the medical domain.”
Hidden stratification causes clinically meaningful failures in machine learning for medical imaging (2019, methodology): “As a result, medical imagery analysts have commonly begun either to use semi-automated labelling techniques [10, 14, 18, 35] or to apply human expertise to produce a narrow or incomplete set of visual labels [26] rather than exhaustively labelling all possible findings and variations.”