ArticleJournal of imaging2026
Towards Automated Spine Fracture Detection on Whole-Body CT of Polytraumatized Patients.
Article in Journal of imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Treatment of severely injured patients is challenging, and timely reading of whole-body computed tomography (WBCT) images therefore crucial. Artificial intelligence is increasingly used to prioritize and detect acute injuries in this context. Algorithms focusing on the cervical spine and compression fractures have been deployed successfully. However, tools for whole spine assessment and the entirety of fracture morphologies are lacking. We aimed to investigate the capabilities of an algorithm to detect spine fractures on WBCTs and factors contributing to the difficulties in its development. A version 1.0 (v1) of the algorithm was previously trained with 454 cervical spine fractures using a U-Net via four-fold cross-validation to segment spine fractures and the spine via a multi-task loss. Further training expanded towards whole spine assessment with additional annotated fractures (Cohort 1) of the cervical (
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