AAPM CT metal artifact reduction grand challenge
The CT-MAR grand challenge provided an opportunity to benchmark state-of-the-art MAR algorithms. Our hybrid data generation framework was a powerful tool for simulating large-scale realistic datasets for MAR algorithm development. A clinically relevant universal MAR benchmark offered an objective and meaningful way to compare different approaches. The training data and benchmark were published online to support future MAR development.
Authors
- Hyoung Suk Park (ORCID: https://orcid.org/0000-0003-0032-4630)
- Fuxin Fan
- Mareike Thies (ORCID: https://orcid.org/0000-0002-1364-4337)
- Nils Peters (ORCID: https://orcid.org/0000-0003-0860-5517)
- Eri Haneda
- Harald Paganetti (ORCID: https://orcid.org/0000-0002-6257-2413)
- Wenjun Xia (ORCID: https://orcid.org/0000-0002-0428-1490)
- Grigorios Marios Karageorgos (ORCID: https://orcid.org/0000-0002-0234-3109)
- Jianhua Ma (ORCID: https://orcid.org/0000-0003-4519-821X)
- Bruno De Man (ORCID: https://orcid.org/0000-0001-7250-3406)
- Kiwan Jeon (ORCID: https://orcid.org/0000-0002-2460-7478)
- Ge Wang (ORCID: https://orcid.org/0000-0002-2656-7705)
- Jiayong Zhang (ORCID: https://orcid.org/0000-0001-9080-3373)
- Yi Guo (ORCID: https://orcid.org/0000-0002-0875-737X)
Institutions
- Harvard University (US)
- Rensselaer Polytechnic Institute (US)
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- Massachusetts General Hospital (US)
- Fred Hutch Cancer Center (US)
- GE Global Research (United States) (US)
- National Institute for Mathematical Sciences (KR)
- Southern Medical University (CN)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1002/mp.70050
- Citations
- 3
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.02