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physics.med-ph2025
Pseudoinverse Diffusion Models for Generative CT Image Reconstruction from Low Dose Data
Matthew Tivnan, Dufan Wu, Quanzheng Li
Score-based diffusion models have significantly advanced generative deep learning for image processing. Measurement conditioned models have also been applied to inverse problems su…
physics.med-ph2025
Generative Super-Resolution PET Imaging with Fourier Diffusion Models
Matthew Tivnan, Quanzheng Li
Neurological Positron Emission Tomography (PET) is a critical imaging modality for diagnosing and studying neurodegenerative diseases like Alzheimer's disease. However, the inheren…
physics.med-ph2024★ 2 cited
Hallucination Index: An Image Quality Metric for Generative Reconstruction Models
Matthew Tivnan, Siyeop Yoon, Zhennong Chen +3
Generative image reconstruction algorithms such as measurement conditioned diffusion models are increasingly popular in the field of medical imaging. These powerful models can tran…