Diagnostic performance and confidence of an optimized deep-learning algorithm for the detection of intracranial hemorrhages
Potentially life-threatening intracranial hemorrhages are time-critical and need accurate detection on non-contrast cranial CT. The optimized algorithm achieved high diagnostic accuracy for ICH detection similar to radiologists. The combination of radiologists and AI may improve the efficiency and diagnostic quality of ICH detection.
Authors
- Julius F. Heidenreich (ORCID: https://orcid.org/0000-0002-0683-7982)
- Philipp Gruschwitz (ORCID: https://orcid.org/0000-0002-2565-8111)
- Thorsten Alexander Bley (ORCID: https://orcid.org/0000-0001-9311-7985)
- Jan-Lucca Hennes
- Kristina Krompaß
- Jan-Peter Grunz
- Franziska Tombach
- Anna Weber
- Henner Huflage
Institutions
- Universitätsklinikum Würzburg (DE)
Publication Details
- Journal
- Insights into Imaging
- Published
- 2026-03-17
- DOI
- https://doi.org/10.1186/s13244-026-02249-w
- Primary Topic
- Intracerebral and Subarachnoid Hemorrhage Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00