PADM: A Physics-aware Diffusion Model for Attenuation Correction

• URL: http://arxiv.org/abs/2511.06948v1
• Date: Mon, 10 Nov 2025 10:54:46 GMT
• Title: PADM: A Physics-aware Diffusion Model for Attenuation Correction
• Authors: Trung Kien Pham, Hoang Minh Vu, Anh Duc Chu, Dac Thai Nguyen, Trung Thanh Nguyen, Thao Nguyen Truong, Mai Hong Son, Thanh Trung Nguyen, Phi Le Nguyen,
• Abstract summary: Attenuation artifacts remain a significant challenge in cardiac Myocardial Perfusion Imaging (MPI) using Single-Photon Emission Computed Tomography (SPECT)<n>In this study, we propose a novel CT-free solution to attenuation correction in cardiac SPECT.<n>Specifically, we introduce Physics-aware Attenuation Correction Diffusion Model (PADM), a diffusion-based generative method that incorporates explicit physics priors via a teacher--student distillation mechanism.
• Score: 5.394088312094123
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Attenuation artifacts remain a significant challenge in cardiac Myocardial Perfusion Imaging (MPI) using Single-Photon Emission Computed Tomography (SPECT), often compromising diagnostic accuracy and reducing clinical interpretability. While hybrid SPECT/CT systems mitigate these artifacts through CT-derived attenuation maps, their high cost, limited accessibility, and added radiation exposure hinder widespread clinical adoption. In this study, we propose a novel CT-free solution to attenuation correction in cardiac SPECT. Specifically, we introduce Physics-aware Attenuation Correction Diffusion Model (PADM), a diffusion-based generative method that incorporates explicit physics priors via a teacher--student distillation mechanism. This approach enables attenuation artifact correction using only Non-Attenuation-Corrected (NAC) input, while still benefiting from physics-informed supervision during training. To support this work, we also introduce CardiAC, a comprehensive dataset comprising 424 patient studies with paired NAC and Attenuation-Corrected (AC) reconstructions, alongside high-resolution CT-based attenuation maps. Extensive experiments demonstrate that PADM outperforms state-of-the-art generative models, delivering superior reconstruction fidelity across both quantitative metrics and visual assessment.

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