Automated quantification of lung pathology on micro-CT in diverse disease models using deep learning
This research was supported by the Service Public de Wallonie (AEROVID grant to FB, WV) and The Flemish Research Foundation (FWO, doctoral mandate 1SF2224N to EV and 1186121N/1186123N to LS, infrastructure grant I006524N to GVV).
Authors
- Wim Vos (ORCID: https://orcid.org/0000-0003-0827-421X)
- Frederik Maes (ORCID: https://orcid.org/0000-0003-0027-1479)
- Eliane Vanhoffelen (ORCID: https://orcid.org/0000-0003-1938-254X)
- Birger Tielemans (ORCID: https://orcid.org/0000-0002-1775-1797)
- Greetje Vande Velde (ORCID: https://orcid.org/0000-0002-5633-3993)
- Flore Belmans (ORCID: https://orcid.org/0000-0002-8944-6898)
- Laura Seldeslachts (ORCID: https://orcid.org/0000-0002-9562-2923)
Institutions
- University of Liège (BE)
- VIB-KU Leuven Center for Microbiology (BE)
- RWTH Aachen University (DE)
- KU Leuven (BE)
Publication Details
- Journal
- EBioMedicine
- Published
- 2025-08-30
- DOI
- https://doi.org/10.1016/j.ebiom.2025.105904
- Citations
- 1
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.52
Funders
- Fonds Wetenschappelijk Onderzoek
- Service Public de Wallonie