Deep-learning based automated pancreas segmentation on CT scans of chronic pancreatitis patients
The AI model demonstrated high accuracy and robustness in pancreas segmentation of both CP patients and healthy subjects, and across diverse sites and scanners, suggesting its potential for clinical application.
Authors
- Marjolein Henrieke Liedenbaum
- Søren Schou Olesen (ORCID: https://orcid.org/0000-0003-3916-3168)
- Surenth Nalliah
- Jens Brøndum Frøkjær (ORCID: https://orcid.org/0000-0001-8722-0070)
- Asbjørn Mohr Drewes (ORCID: https://orcid.org/0000-0001-7465-964X)
- Ingfrid Helene Salvesen Haldorsen
- Trond Engjom (ORCID: https://orcid.org/0000-0002-2207-5455)
- Erlend Hodneland (ORCID: https://orcid.org/0000-0003-2828-1521)
- Esben Bolvig Mark (ORCID: https://orcid.org/0000-0002-4176-7430)
- Thomas Hellström (ORCID: https://orcid.org/0000-0001-7242-2200)
- Mille Kristence Lillien Mosegaard
Institutions
- Aalborg University Hospital (DK)
- Haukeland University Hospital (NO)
- Aalborg University (DK)
Publication Details
- Journal
- European Journal of Radiology
- Published
- 2025-05-14
- DOI
- https://doi.org/10.1016/j.ejrad.2025.112175
- Citations
- 2
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 2.72