Development and validation of a keypoint region-based convolutional neural network to automate thoracic Cobb angle measurements using whole-spine standing radiographs
This method will enable fast and accurate screening for AIS and assessment of postoperative outcomes and provides a development framework for further automation and validation of spinopelvic measurements.
Authors
- Jaskeerat Gujral (ORCID: https://orcid.org/0009-0003-3626-0306)
- Jonathan Sussman (ORCID: https://orcid.org/0000-0002-7702-8816)
- Marie Kerr
- William C. Welch (ORCID: https://orcid.org/0000-0002-1665-7985)
- Patrick J. Cahill (ORCID: https://orcid.org/0000-0002-7129-1007)
- Beth A. Winkelstein (ORCID: https://orcid.org/0000-0003-0414-0484)
- Jang W. Yoon (ORCID: https://orcid.org/0000-0003-2705-0406)
- Bhargavi R. Budihal
- Mert Marcel Dagli (ORCID: https://orcid.org/0000-0002-5201-6720)
- Ali K. Ozturk (ORCID: https://orcid.org/0000-0001-6474-9422)
- Jason Anari
Institutions
- Institute of Medical Sciences (IN)
- University of Pennsylvania (US)
Publication Details
- Journal
- Acta Neurochirurgica
- Published
- 2025-08-22
- DOI
- https://doi.org/10.1007/s00701-025-06645-x
- Primary Topic
- Scoliosis diagnosis and treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health