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20112026
most citedPlug-and-Play Methods for Integrating Physical and Learned Models in Computational Imaging

221 citations · 1.5k across the 104 of their papers we have counts for

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14 papers · 1 filter

eess.IV2024★ 2 cited

A Generalizable 3D Diffusion Framework for Low-Dose and Few-View Cardiac SPECT

Huidong Xie, Weijie Gan, Wei Ji +13

Myocardial perfusion imaging using SPECT is widely utilized to diagnose coronary artery diseases, but image quality can be negatively affected in low-dose and few-view acquisition…

eess.IV2024★ 2 cited

Plug-and-Play Priors as a Score-Based Method

Chicago Y. Park, Yuyang Hu, Michael T. McCann +3

Plug-and-play (PnP) methods are extensively used for solving imaging inverse problems by integrating physical measurement models with pre-trained deep denoisers as priors. Score-ba…

eess.IV2024

Closed-Form Approximation of the Total Variation Proximal Operator

Edward P. Chandler, Shirin Shoushtari, Brendt Wohlberg +1

Total variation (TV) is a widely used function for regularizing imaging inverse problems that is particularly appropriate for images whose underlying structure is piecewise constan…

eess.IV2024

ADOBI: Adaptive Diffusion Bridge For Blind Inverse Problems with Application to MRI Reconstruction

Yuyang Hu, Albert Peng, Weijie Gan +1

Diffusion bridges (DB) have emerged as a promising alternative to diffusion models for imaging inverse problems, achieving faster sampling by directly bridging low- and high-qualit…

eess.IV2024

FiRe: Fixed-points of Restoration Priors for Solving Inverse Problems

Matthieu Terris, Ulugbek S. Kamilov, Thomas Moreau

Selecting an appropriate prior to compensate for information loss due to the measurement operator is a fundamental challenge in imaging inverse problems. Implicit priors based on d…

cs.CV2024

Random Walks with Tweedie: A Unified View of Score-Based Diffusion Models

Chicago Y. Park, Michael T. McCann, Cristina Garcia-Cardona +2

We present a concise derivation for several influential score-based diffusion models that relies on only a few textbook results. Diffusion models have recently emerged as powerful…