{"url":"/dataset/skm-tea","name":"SKM-TEA","full_name":"Stanford Knee MRI with Multi-Task Evaluation","description_markdown":"The **SKM-TEA** dataset pairs raw quantitative knee MRI (qMRI) data, image data, and dense labels of tissues and pathology for end-to-end exploration and evaluation of the MR imaging pipeline.  This 1.6TB dataset consists of raw-data measurements of ~25,000 slices (155 patients) of anonymized patient knee MRI scans, the corresponding scanner-generated DICOM images, manual segmentations of four tissues, and bounding box annotations for sixteen clinically relevant pathologies.\r\n\r\n## Challenge Tracks\r\n**DICOM Track**: The DICOM benchmarking track uses scanner-generated DICOM images as the input for image segmentation and detection tasks.\r\n\r\n**Raw Data Track**: The Raw Data benchmarking track uses raw MRI data (i.e. k-space) as the input for image reconstruction, segmentation and detection tasks.","description_withheld":null,"homepage":"https://github.com/StanfordMIMI/skm-tea","introduced_date":"2022-03-14","introduced_date_note":null,"introduced_by":{"paper":"/paper/skm-tea-a-dataset-for-accelerated-mri","title":"SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation","first_author":"Arjun D Desai","url":null},"license":{"name":"Stanford University Dataset Research Use Agreement","url":"https://stanfordaimi.azurewebsites.net/datasets/4aaeafb9-c6e6-4e3c-9188-3aaaf0e0a9e7"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Medical","url":"/datasets/modality/medical"},{"name":"MRI","url":"/datasets/modality/mri"}],"tasks":[{"name":"MRI Reconstruction","url":"/task/mri-reconstruction","datasets_with_task":"/datasets/task/mri-reconstruction"},{"name":"Medical Object Detection","url":"/task/medical-object-detection","datasets_with_task":"/datasets/task/medical-object-detection"},{"name":"3D Medical Imaging Segmentation","url":"/task/3d-medical-imaging-segmentation","datasets_with_task":"/datasets/task/3d-medical-imaging-segmentation"},{"name":"MRI segmentation","url":"/task/mri-segmentation","datasets_with_task":"/datasets/task/mri-segmentation"}],"languages":[],"variants":["SKM-TEA"],"data_loaders":[],"num_papers_in_archive":16,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}