The dataset contains MRI images of the lumbar vertebras and lumbar discs, focusing on the vertebras and lumbar intervertebral discs. The scans are accompanied by medical reports to aid in diagnosing spine diseases such as degenerative spine conditions, lumbar degenerative disorders, and disc herniations. This dataset emphasizes spine magnetic resonance imaging of the lumbar region and spinal canal, capturing detailed imaging using sagittal T2-weighted images.
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The dataset supports segmentation algorithms and classification models, aiming for accurate automatic segmentations and classification results. Deep learning techniques can be applied to medical images to assess spinal stenosis, detect degenerative changes, and segment spinal structures. The spinal pathology covered includes conditions like spinal cord compression, canal stenosis, and other lumbar spinal disorders. The dataset includes both sagittal views and axial views, making it suitable for machine learning and medical diagnosis tasks.
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formats.All patients consented to the publication of data. All data is de-identified.
This multi-center lumbar dataset is invaluable for exploring disc disease, back pain, and degenerative changes. It offers rich diagnostic imaging data and benchmark performance values for classification models and segmentation challenges in spinal pathology analysis.
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