Deformable image registration of dark‐field chest radiographs for functional lung assessment
Our regional characterization of lung dark-field signal changes between the breathing states via deformable image registration provides a proof-of-principle that dynamic radiography-based lung function assessment approaches may benefit from considering registered dark-field images in addition to standard plain chest radiographs. This opens up new options for low-dose and rapid lung ventilation assessment via dark-field chest radiography that has the potential to improve lung diagnostics considerably.
Authors
- Henriette Bast (ORCID: https://orcid.org/0009-0001-7390-1809)
- Daniela Pfeiffer (ORCID: https://orcid.org/0000-0003-2002-8337)
- Vasiliki Sideri‐Lampretsa (ORCID: https://orcid.org/0000-0003-0135-7442)
- Thomas Koehler (ORCID: https://orcid.org/0000-0002-1986-0057)
- Florian T. Gassert (ORCID: https://orcid.org/0000-0003-4126-462X)
- Alexander Wolfgang Marka (ORCID: https://orcid.org/0000-0002-2111-8177)
- Daniel Rueckert
- Fabian Drexel
Institutions
- TUM Klinikum (DE)
- Institute for Advanced Study (DE)
- Philips (Germany) (DE)
- Munich Center for Machine Learning
- Imperial College London (GB)
- Technical University of Munich (DE)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-08-01
- DOI
- https://doi.org/10.1002/mp.18023
- Primary Topic
- Advanced X-ray Imaging Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Australian Government
- Bundesministerium für Bildung und Forschung
- Technische Universität München
- Centre for Advanced Laser Applications
- European Research Council