Lumbar spine segmentation in MR images: a dataset and a public benchmark

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This paper presents a large publicly available multi-center lumbar spine magnetic resonance imaging (MRI) dataset with reference segmentations of vertebrae, intervertebral discs (IVDs), and spinal canal.

• The dataset includes 447 sagittal T1 and T2 MRI series from 218 patients with a history of low back pain and was collected from four different hospitals.
• An iterative data annotation approach was used by training a segmentation algorithm on a small part of the dataset, enabling semi-automatic segmentation of the remaining images.
• The algorithm provided an initial segmentation, which was subsequently reviewed, manually corrected, and added to the training data.