A frozen diffusion PET model outfitted with a low-rank nuclear transformer and dose-specific encoding controllers reconstructs ultra-low-dose images and selects the right controller when the dose is unknown.
Brain PET Synthesis from MRI Using Joint Probability Distribution of Diffusion Model at Ultrahigh Fields
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abstract
MRI and PET are important modalities and can provide complementary information for the diagnosis of brain diseases because MRI can provide structural information of brain and PET can obtain functional information of brain. However, PET is usually missing. Especially, simultaneous PET and MRI imaging at ultrahigh field is not achievable in the current. Thus, synthetic PET using MRI at ultrahigh field is essential. In this paper, we synthetic PET using MRI as a guide by joint probability distribution of diffusion model (JPDDM). Meanwhile, We utilized our model in Ultrahigh Fields.
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Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction
A frozen diffusion PET model outfitted with a low-rank nuclear transformer and dose-specific encoding controllers reconstructs ultra-low-dose images and selects the right controller when the dose is unknown.