5 papers
Minimax Multi-Target Conformal Prediction with Applications to Imaging Inverse Problems
Jeffrey Wen, Rizwan Ahmad, Philip Schniter
In ill-posed imaging inverse problems, uncertainty quantification remains a fundamental challenge, especially in safety-critical applications. Recently, conformal prediction has be…
Solving Inverse Problems using Diffusion with Iterative Colored Renoising
Matt C. Bendel, Saurav K. Shastri, Rizwan Ahmad +1
Imaging inverse problems can be solved in an unsupervised manner using pre-trained diffusion models, but doing so requires approximating the gradient of the measurement-conditional…
Groupwise Image Registration with Edge-Based Loss for Low-SNR Cardiac MRI
Xuan Lei, Philip Schniter, Chong Chen +1
Purpose: To perform image registration and averaging of multiple free-breathing single-shot cardiac images, where the individual images may have a low signal-to-noise ratio (SNR).…
Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems
Jeffrey Wen, Rizwan Ahmad, Philip Schniter
In imaging inverse problems, we would like to know how close the recovered image is to the true image in terms of full-reference image quality (FRIQ) metrics like PSNR, SSIM, LPIPS…
pcaGAN: Improving Posterior-Sampling cGANs via Principal Component Regularization
Matthew C. Bendel, Rizwan Ahmad, Philip Schniter
In ill-posed imaging inverse problems, there can exist many hypotheses that fit both the observed measurements and prior knowledge of the true image. Rather than returning just one…