How-to
Upload a zip file containing DICOM files below. The scan will then be processed, typically within 1 minute. For each scan, this demo produces radiological gradings described in the main page. When a scan is processed, this page will automatically be redirected to results page. You can also enter in your e-mail address where we will send you an e-mail containing a link to the results.

I have anonymized the scans prior to submission.

(optional)

 

The ZIP file should:

 

Disclaimer
Details

Examples

More Information
More details about this work is available at http://www.robots.ox.ac.uk/~vgg/research/spine/
For any queries or to add your own grading system, contact amirj@robots.ox.ac.uk
References
[1] A. Jamaludin, M. Lootus, T. Kadir, A. Zisserman, J. Urban, M. C. Battié, J. Fairbank, and I. McCall. Issls prize in bioengineering science 2017: Automation of reading of radiological features from magnetic resonance images (mris) of the lumbar spine without human intervention is comparable with an expert radiologist. European Spine Journal, 26(5):1374–1383, May 2017.
[2] A. Jamaludin, T. Kadir, and A. Zisserman. SpineNet: Automated classification and evidence visualization in spinal MRIs. Medical Image Analysis, 41 (Supplement C):63 – 73, 2017.