Zero-TE MRI-based attenuation correction for bone components on chest [18F] FDG PET/MRI: accuracy, repeatability, and external validation of an unsupervised deep learning approach using unpaired PET/CT data
Munenobu Nogami, Hidetoshi Matsuo, Mizuho Nishio, Feibi Zeng, Junko Inoue Inukai, Miho Tachibana, Florian Wiesinger, Sandeep Kaushik, Takako Kurimoto, Kazuhiro Kubo, Martin W. Huellner, Hidehiko Okazawa, Takamichi Murakami · 2026
Read Zero-TE MRI-based attenuation correction for bone components on chest [18F] FDG PET/MRI: accuracy, repeatability, and external validation of an unsupervised deep learning approach using unpaired PET/CT data by Munenobu Nogami, Hidetoshi Matsuo, Mizuho Nishio, Feibi Zeng, Junko Inoue Inukai, Miho Tachibana, Florian Wiesinger, Sandeep Kaushik, Takako Kurimoto, Kazuhiro Kubo, Martin W. Huellner, Hidehiko Okazawa, Takamichi Murakami (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13388429.txt.
Description
Munenobu Nogami and co-authors improve a step in chest scans that blend two imaging methods. PET scans need a correction map to read uptake values right, and MRI data must stand in for CT data to build it. Bone in the chest is hard to separate, and matched training pairs are scarce since breathing shifts the body.
The team trained a learning model on unpaired scans from many patients to fake CT maps from a fast MRI mode. In tests, the new maps matched CT-based maps for the spine better than the standard method. Uptake values in bone also sat closer to the CT-based values. Repeat scans and data from another site held up, which supports wider use.
Catalog record
| CREATOR | Munenobu Nogami, Hidetoshi Matsuo, Mizuho Nishio, Feibi Zeng, Junko Inoue Inukai, Miho Tachibana, Florian Wiesinger, Sandeep Kaushik, Takako Kurimoto, Kazuhiro Kubo, Martin W. Huellner, Hidehiko Okazawa, Takamichi Murakami |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 40 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |