A hybrid training database and evaluation benchmark for assessing metal artifact reduction methods for X‐ray CT imaging
We developed and distributed tools and datasets for the development and evaluation of MAR algorithms. This is the first comprehensive evaluation benchmark covering a large number of clinically realistic metal artifact scenarios.
Authors
- Nils Peters (ORCID: https://orcid.org/0000-0003-0860-5517)
- Harald Paganetti (ORCID: https://orcid.org/0000-0002-6257-2413)
- Wenjun Xia (ORCID: https://orcid.org/0000-0002-0428-1490)
- Eri Haneda (ORCID: https://orcid.org/0000-0003-2660-9028)
- Grigorios Marios Karageorgos (ORCID: https://orcid.org/0000-0002-0234-3109)
- Joost Verburg (ORCID: https://orcid.org/0000-0002-7084-1193)
- Bruno De Man (ORCID: https://orcid.org/0000-0001-7250-3406)
- Ge Wang (ORCID: https://orcid.org/0000-0002-7516-2341)
- Jiayong Zhang (ORCID: https://orcid.org/0000-0001-9080-3373)
Institutions
- Rensselaer Polytechnic Institute (US)
- Massachusetts General Hospital (US)
- Fred Hutch Cancer Center (US)
- GE Global Research (United States) (US)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1002/mp.70020
- Citations
- 2
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.35