Aug 2026· Medical Physics (Lancaster)· Vol 53· 0 citations· 65 references
Medicine
TL;DR
Current deep learning methods use non‐attenuation corrected (NAC) PET data to predict CT‐like or directly AC‐PET images, but their dependence on emission characteristics limits generalizability across tracers and anatomical coverage.
Abstract
Accurate attenuation correction (AC) is essential for quantitative positron emission tomography (PET). Conventional CT‐based AC provides reliable attenuation (μ‐) maps but adds radiation, introduces PET/CT misalignment artifacts, and is unavailable on stand‐alone PET systems. Existing deep learning (DL) methods use non‐attenuation corrected (NAC) PET data to predict CT‐like or directly AC‐PET images, but their dependence on emission characteristics limits generalizability across tracers and anatomical coverage, especially for long axial field‐of‐view PET.
We participated in the BIC-MAC Challenge with a multimodal 3D patch-based U-Net for pseudo-CT generation from NAC-PET, MRI, and 2D topograms. By using separate PET and MR encoders, multi-scale feature fusion, and FiLM-based topogram conditioning at the bottleneck, we obtain a model that integrates complementary cross-m...
R. Bell, Artemis Bouzaki, Jia-Ming Cao et al.· 0 citations
BACKGROUND
Accurate attenuation correction (AC) is essential for quantification in [18F]FDG PET imaging. However, CT or MRI-based methods may introduce artifacts, prolong scan duration, or increase radiation exposure. Deep learning-based AC (DLAC) has emerged as an alternative, enabling the generation of attenuation-co...
Atefeh Tahmasebzadeh, P. Ghafarian, M. Sadeghi· Applied Radiation and Isotop...· 0 citations
OBJECTIVE
Positron emission tomography (PET) provides essential functional information for disease assessment. However, reducing injected activity or acquisition time produces low-dose (LD) PET with stronger count-dependent noise and less reliable uptake quantification. Diffusion models offer a promising solution for P...
Xue-Peng Liu, Rui-Li Li, Ze-Tong Liu et al.· Physics in Medicine and Biol...· 0 citations
Fluorodeoxyglucose (FDG) positron emission tomography (PET) is widely used for detecting metabolic changes associated with neurodegeneration in Alzheimer's disease (AD) and other dementias but is costly and involves ionizing radiation. Here we developed SynthPET, a multimodal deep learning framework that synthesizes FD...
Xavier Beltran-Urbano, Katie R. Jobson, I. Nasrallah et al.· Alzheimer's & Dementia· 0 citations
In PET/CT imaging, CT frequently accounts for more than 50% of the total radiation exposure, even when used solely for attenuation correction and anatomical localisation. This poses a major limitation for dose-sensitive populations, including pregnant women and paediatric patients. This study systematically evalu...
Georgios I. Angelis, Y. Gholami, K. Willowson et al.· EJNMMI Physics· 0 citations
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