Paired PET‐MRI Deep Learning Model for Translating [ <sup>11</sup> C]PiB to [ <sup>18</sup> F]Florbetaben Amyloid Images
The DCNv3-based U-Net demonstrated high performance in metrics measurement and statistical analyses for the PET image-to-image translation task. This work also justified the importance of MR images in providing structural information.
Authors
- Ing‐Tsung Hsiao (ORCID: https://orcid.org/0000-0002-5255-7498)
- Shao‐Yi Huang (ORCID: https://orcid.org/0000-0002-0305-3269)
- Hanwei Wang (ORCID: https://orcid.org/0000-0001-8242-7806)
- Kevin T. Chen (ORCID: https://orcid.org/0000-0001-8556-5307)
- Yunung Nina Lin (ORCID: https://orcid.org/0000-0002-3669-3625)
- Cheng‐Han Tsai
Institutions
- National Taiwan University (TW)
- Chang Gung University (TW)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-11-27
- DOI
- https://doi.org/10.1002/mp.70168
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Health Research Institutes
- National Taiwan University
- National Science and Technology Council