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CT MRI Spine

SpineWeb Dataset 10 (multi-modality vertebra recognition)

SpineWeb Dataset 10: Multi-Modality Vertebra Recognition in Arbitrary Views using 3D Deformable Hierarchical Model

Spine MR and CT images of 20 subjects with manually annotated 3D vertebra center locations and 3D vertebra orientations for every vertebra, released on SpineWeb as a reference for vertebra recognition. Shared after a request form.

Overview

SpineWeb Dataset 10 pairs spine MR and CT images with manual vertebra annotations. It was released on SpineWeb, an online platform for spinal imaging research, as reference data for vertebra recognition: finding where each vertebra is, how it is oriented and which level it is. The data accompanies the 2015 IEEE Transactions on Medical Imaging paper by Cai and colleagues, which matches a 3D deformable hierarchical spine model to MR and CT images taken in arbitrary views.

Composition

The SpineWeb entry lists MR and CT images from 20 subjects. It does not say how many scans each subject has, which spine regions are covered, or whether every subject has both modalities. No sex, age, diagnosis or split breakdown is published. The SpineWeb news feed dates the release to 5 April 2015.

Acquisition

The SpineWeb entry gives no sites, scanners, MR sequences, resolution or file format. The paper evaluates its method on T1 and T2 weighted MR and on CT from several sources, including scans collected in the Ontario area of Canada, but it does not state which of its evaluation images make up the released set.

Annotations

For each vertebra, the 3D center location, placed at the spinal cord, and the 3D orientation of the vertebra were annotated by hand. In the paper, annotators drew a planar bounding box over each vertebra in the sagittal, axial and coronal views and assigned a vertebra label to each box.

Known limitations

  • The only dataset documentation is a short entry on the SpineWeb datasets page. The paper describes the method and its evaluation data, not the released files.
  • No license or terms of use are published. Access starts with a request form that asks for the applicant's institution, a short research description and the principal investigator's contact details.
  • On 2026-10-09 the SpineWeb host name did not resolve, so the facts here come from archived copies of the official pages. Whether the data can still be requested is unknown.

Cohort

Aggregate numbers from the sources below. Bars are relative to the 20 subjects.

Anatomy

subjects

  • Spine 20 100%

License and access

Our reading of the license, not legal advice. Before you use the data, read the original license and confirm that your use is allowed. We take no responsibility for how you use a dataset. Full disclaimer

Access
Application

A research proposal is reviewed and approved

Access page

No published license or data use terms

The data holder has published no license and no data use terms. Any use, sharing or commercial right has to be agreed with the data holder, and nothing can be assumed to be allowed. Default copyright and data protection law still apply.

The SpineWeb entry states no license or terms of use for Dataset 10. It only says that publications using the data may cite the paper by Cai et al. The request form asks for the applicant's institution, a brief description of the research and the details of the project's principal investigator.

Original license text Checked 2026-10-08

What you can do

  • Commercial use Not stated
  • Train ML models Not stated
  • Create derived data Not stated
  • Publish results Not stated

What you can share

  • Share the data Not stated
  • Share derived data Not stated
  • Share trained models Not stated

What you must do

  • Cite or credit Not stated
  • Share alike Not stated
  • Sign an agreement Not stated
  • Ethics approval Not stated
  • Manuscript review Not stated
  • Release code Not stated
  • Return results Not stated
  • Delete after use Not stated

Limits

  • No re-identification Not stated
  • Location limits Not stated

Citation

Yunliang Cai, Said Osman, Manas Sharma, Mark Landis, and Shuo Li, "Multi-Modality Vertebra Recognition in Arbitrary Views using 3D Deformable Hierarchical Model", IEEE Transactions on Medical Imaging, 2015.

All numbers

Every number on this page, as stored in stats.csv, with its source.

MeasureBreakdownValueSource
Subjectstotal
Listed as MR and CT images from 20 subjects
20spineweb-datasets-2024
Dataset 10
Subjectsanatomy=spine 20spineweb-datasets-2024
Dataset 10

Sources

The keys used in the table above.