1 citations · 1 across the 3 of their papers we have counts for
3 papers
physics.med-ph2024
Multi-Subject Image Synthesis as a Generative Prior for Single-Subject PET Image Reconstruction
George Webber, Yuya Mizuno, Oliver D. Howes +3
Large high-quality medical image datasets are difficult to acquire but necessary for many deep learning applications. For positron emission tomography (PET), reconstructed image qu…
physics.med-ph2024★ 1 cited
Generative-Model-Based Fully 3D PET Image Reconstruction by Conditional Diffusion Sampling
George Webber, Yuya Mizuno, Oliver D. Howes +3
Score-based generative models (SGMs) have recently shown promising results for image reconstruction on simulated positron emission tomography (PET) datasets. In this work we have d…
eess.IV2023
Self-Supervised and Supervised Deep Learning for PET Image Reconstruction
Andrew J. Reader
A unified self-supervised and supervised deep learning framework for PET image reconstruction is presented, including deep-learned filtered backprojection (DL-FBP) for sinograms, d…