Deep learning estimation of proton stopping power with photon-counting computed tomography: a virtual study
These early results show promise for using a combination of PCCT and deep learning for estimating SPR, which in extension demonstrates potential for reducing the beam range uncertainty in proton therapy.
Authors
- Erik Fredenberg (ORCID: https://orcid.org/0000-0002-0724-0205)
- Andrea Scotti (ORCID: https://orcid.org/0000-0003-4731-4384)
- Ruihan Huang (ORCID: https://orcid.org/0009-0009-3510-9026)
- Mats Persson (ORCID: https://orcid.org/0000-0002-5092-8822)
- Karin Larsson (ORCID: https://orcid.org/0000-0002-6403-2736)
- Dennis Hein (ORCID: https://orcid.org/0000-0002-7463-7966)
- Jonas Andersson (ORCID: https://orcid.org/0000-0002-1635-7229)
- D. Collin
Institutions
- Karolinska University Hospital (SE)
- Healthcare in Sweden (SE)
- KTH Royal Institute of Technology (SE)
- Umeå University (SE)
Publication Details
- Journal
- Journal of Medical Imaging
- Published
- 2024-11-20
- DOI
- https://doi.org/10.1117/1.jmi.11.s1.s12809
- Citations
- 1
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.18
Funders
- Göran Gustafssons Stiftelser
- Stiftelsen för Strategisk Forskning
- Cancerfonden
- Vetenskapsrådet
- China Scholarship Council