The Duke University Cervical Spine MRI Segmentation Dataset (CSpineSeg)

Scientific Data

Longfei Zhou, Walter Wiggins, Jikai Zhang, Roy Colglazier, Jay Willhite, Austin Dixon, Michael Malinzak, Hanxue Gu, Maciej A. Mazurowski & Evan Calabrese

An Example of the sagittal T2 MRI with human annotations of vertebral bodies (red) and intervertebral discs (green) and a zoomed-in view for the C5-C7 region.

Summary

This work describes a publicly available dataset, the Duke University Cervical Spine MRI Segmentation Dataset (CSpineSeg), consisting of 1,255 cervical spine magnetic resonance imaging (MRI) examinations from 1,232 patients collected from the Duke University Health System. CSpineSeg also includes expert manual semantic segmentations of vertebral bodies and intervertebral discs for 481 patients. This dataset aims to provide a resource for training and evaluation of deep learning segmentation models and facilitate cervical spine research. Along with the dataset, we present a deep learning segmentation model which could be used as a benchmark in cervical spine segmentation tasks. Our segmentation model achieves a Dice Coefficient of 0.916, demonstrating the feasibility of utilizing CSpineSeg to train segmentation models.

Citation

Zhou, Longfei, et al. “The Duke University Cervical Spine MRI Segmentation Dataset (CSpineSeg).” Scientific Data 12.1 (2025): 1695.

BibTex

@article{zhou2025duke, title={The Duke University Cervical Spine MRI Segmentation Dataset (CSpineSeg)}, author={Zhou, Longfei and Wiggins, Walter and Zhang, Jikai and Colglazier, Roy and Willhite, Jay and Dixon, Austin and Malinzak, Michael and Gu, Hanxue and Mazurowski, Maciej A and Calabrese, Evan}, journal={Scientific Data}, volume={12}, number={1}, pages={1695}, year={2025}, publisher={Nature Publishing Group UK London} }

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