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Generative Translation Priors: Bayesian Imaging with Cross-Modality Image Translation
Evan Bell, Jiaming Liu, Yifan Chen +1
The ability to leverage images from co-available modalities to inform target-domain reconstruction is highly desirable in imaging algorithms. In this work, we introduce Generative…
PRISM: Probabilistic and Robust Inverse Solver with Measurement-Conditioned Diffusion Prior for Blind Inverse Problems
Yuanyun Hu, Evan Bell, Guijin Wang +1
Diffusion models are now commonly used to solve inverse problems in computational imaging. However, most diffusion-based inverse solvers require complete knowledge of the forward o…
Ultrasound Report Generation with Multimodal Large Language Models for Standardized Texts
Peixuan Ge, Tongkun Su, Faqin Lv +8
Ultrasound (US) report generation is a challenging task due to the variability of US images, operator dependence, and the need for standardized text. Unlike X-ray and CT, US imagin…
Whitened Score Diffusion: A Structured Prior for Imaging Inverse Problems
Jeffrey Alido, Tongyu Li, Yu Sun +1
Conventional score-based diffusion models (DMs) may struggle with anisotropic Gaussian diffusion processes due to the required inversion of covariance matrices in the denoising sco…
Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors
Zihui Wu, Yu Sun, Yifan Chen +3
Diffusion models (DMs) have recently shown outstanding capabilities in modeling complex image distributions, making them expressive image priors for solving Bayesian inverse proble…
Provable Probabilistic Imaging using Score-Based Generative Priors
Yu Sun, Zihui Wu, Yifan Chen +2
Estimating high-quality images while also quantifying their uncertainty are two desired features in an image reconstruction algorithm for solving ill-posed inverse problems. In thi…