公开最大规模腰椎退行性病变MRI数据集，助力AI诊断研究。
The RSNA Lumbar Degenerative Imaging Spine Classification (LumbarDISC) Dataset
- 整合8国5大洲8家机构2697例患者影像，标注退变程度。
- 每例包含8593个序列，覆盖腰椎各节段狭窄分级。
- 专家标注，免费开放，适合医学AI与影像研究者使用。
RSNA腰椎退行性影像分类（LumbarDISC）数据集是目前最大且公开可用的成人腰椎MRI数据集，专为退行性改变标注。数据涵盖来自全球6个国家、5大洲8个机构的2,697名患者，共8,593个影像序列。该数据集由RSNA、ASNR及ASISR的神经放射科与骨科放射科专家志愿者完成标注，用于2024年RSNA腰椎退行性分类竞赛，旨在评估脊髓管、小关节窝及神经孔狭窄程度。数据集通过Kaggle和RSNA MIRA平台免费提供非商业用途。其目标是推动机器学习在腰椎影像中的应用，提升临床诊疗效率与患者护理水平。
原文摘要 · Abstract (English)
The Radiological Society of North America (RSNA) Lumbar Degenerative Imaging Spine Classification (LumbarDISC) dataset is the largest publicly available dataset of adult MRI lumbar spine examinations annotated for degenerative changes. The dataset includes 2,697 patients with a total of 8,593 image series from 8 institutions across 6 countries and 5 continents. The dataset is available for free for non-commercial use via Kaggle and RSNA Medical Imaging Resource of AI (MIRA). The dataset was created for the RSNA 2024 Lumbar Spine Degenerative Classification competition where competitors developed deep learning models to grade degenerative changes in the lumbar spine. The degree of spinal canal, subarticular recess, and neural foraminal stenosis was graded at each intervertebral disc level in the lumbar spine. The images were annotated by expert volunteer neuroradiologists and musculoskeletal radiologists from the RSNA, American Society of Neuroradiology, and the American Society of Spine Radiology. This dataset aims to facilitate research and development in machine learning and lumbar spine imaging to lead to improved patient care and clinical efficiency.
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