13 citations · 21 across the 4 of their papers we have counts for
4 papers
Analyzing Model Misspecification in Quantitative MRI: Application to Perfusion ASL
Jiachen Wang, Jon Tamir, Adam Bush
Quantitative MRI (qMRI) involves parameter estimation governed by an explicit signal model. However, these models are often confounded and difficult to validate in vivo. A model is…
Robust multi-coil MRI reconstruction via self-supervised denoising
Asad Aali, Marius Arvinte, Sidharth Kumar +2
We study the effect of incorporating self-supervised denoising as a pre-processing step for training deep learning (DL) based reconstruction methods on data corrupted by Gaussian n…
Solving Inverse Problems with Score-Based Generative Priors learned from Noisy Data
Asad Aali, Marius Arvinte, Sidharth Kumar +1
We present SURE-Score: an approach for learning score-based generative models using training samples corrupted by additive Gaussian noise. When a large training set of clean sample…
Few-Max: Few-Shot Domain Adaptation for Unsupervised Contrastive Representation Learning
Ali Lotfi Rezaabad, Sidharth Kumar, Sriram Vishwanath +1
Contrastive self-supervised learning methods learn to map data points such as images into non-parametric representation space without requiring labels. While highly successful, cur…