Artificial intelligence-based analysis and diagnosis of intradural extramedullary spinal tumors by stimulated Raman histology
Our findings confirm the feasibility and effectiveness of AI-assisted SRH analysis for distinguishing IDEM tumor types. This approach may complement conventional intraoperative neuropathology by providing rapid, reliable, and clinically actionable diagnostic information.
Authors
- Pierre Scheffler (ORCID: https://orcid.org/0000-0002-6596-456X)
- Nicolas Neidert (ORCID: https://orcid.org/0000-0003-0299-1138)
- Daniel Erny (ORCID: https://orcid.org/0000-0001-6000-8838)
- Amir El Rahal (ORCID: https://orcid.org/0000-0002-8250-5883)
- Jürgen Beck (ORCID: https://orcid.org/0000-0002-7687-6098)
- Marco Prinz
- Jakob Straehle (ORCID: https://orcid.org/0000-0003-3063-8972)
- Dieter Henrik Heiland (ORCID: https://orcid.org/0000-0002-9258-3033)
- Ulrich Hubbe
- Roland Rölz
Institutions
- Northwestern University (US)
- University of Geneva (CH)
- University of Freiburg (DE)
- German Cancer Research Center (DE)
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- University Medical Center Freiburg (DE)
- Universitätsklinikum Erlangen (DE)
Publication Details
- Journal
- Neuro-Oncology Advances
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1093/noajnl/vdaf211
- Primary Topic
- Medical Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00