Generative adversarial network–based reconstruction of healthy anatomy for anomaly detection in brain CT scans
Without defining anomalies during training, a GAN-based network was used to learn healthy anatomy for brain CT scans. Notably, our approach is not limited to the localization of hemorrhages and tumors and could thus be used to detect structural anatomical changes and other lesions.
Authors
- Stefan Heldmann (ORCID: https://orcid.org/0000-0002-9206-2086)
- Jan Klein (ORCID: https://orcid.org/0000-0001-9421-3549)
- Annika Gerken (ORCID: https://orcid.org/0000-0002-4327-6352)
- Sina Walluscheck (ORCID: https://orcid.org/0000-0003-1270-8340)
- Ivana Galinović (ORCID: https://orcid.org/0000-0003-4904-8251)
- Kersten Villringer (ORCID: https://orcid.org/0000-0003-4192-9193)
- Jochen B. Fiebach (ORCID: https://orcid.org/0000-0002-7936-6958)
Institutions
- Fraunhofer Institute for Digital Medicine (DE)
- Charité - Universitätsmedizin Berlin (DE)
Publication Details
- Journal
- Journal of Medical Imaging
- Published
- 2024-08-09
- DOI
- https://doi.org/10.1117/1.jmi.11.4.044508
- Citations
- 1
- Primary Topic
- Anomaly Detection Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.35
Funders
- Bundesministerium für Bildung und Forschung