MosaicMRI: A Diverse Dataset and Benchmark for Raw Musculoskeletal MRI
Deep learning underpins a wide range of applications in MRI, including reconstruction, artifact removal, and segmentation. However, progress has been driven largely by public datasets focused on brain and knee imaging, shaping how models are trained and evaluated. As a result, careful studies of the reliability of these models across diverse anatomical settings remain limited. In this work, we introduce MosaicMRI, a large and diverse collection of fully sampled raw musculoskeletal (MSK) MR measurements designed for training and evaluating machine-learning--based methods. MosaicMRI is the largest open-source raw MSK MRI dataset to date, comprising 3,150 volumes and 89,830 slices, including...
| Authors | Paula Arguello, Berk Tinaz, Mohammad Shahab Sepehri et al. |
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| Primary category | cs.CV |
| Published | 13 April 2026 |
| Last updated at source | 12 October 2026 |
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