1 citations · 1 across the 3 of their papers we have counts for
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Advancing Positron Emission Tomography Image Quantification: Artificial Intelligence-Driven Methods, Clinical Challenges, and Emerging Opportunities in Long-Axial Field-of-View Positron Emission Tomography/Computed Tomography Imaging
Fereshteh Yousefirizi, Movindu Dassanayake, Alejandro Lopez +6
MTV is increasingly recognized as an accurate estimate of disease burden, which has prognostic value, but its implementation has been hindered by the time-consuming need for manual…
Artificial Intelligence-Guided PET Image Reconstruction and Multi-Tracer Imaging: Novel Methods, Challenges, And Opportunities
Movindu Dassanayake, Alejandro Lopez, Andrew Reader +6
LAFOV PET/CT has the potential to unlock new applications such as ultra-low dose PET/CT imaging, multiplexed imaging, for biomarker development and for faster AI-driven reconstruct…
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…
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…