2 citations · 2 across the 4 of their papers we have counts for
5 papers
Joint Demosaicing and Denoising with Double Deep Image Priors
Taihui Li, Anish Lahiri, Yutong Dai +1
Demosaicing and denoising of RAW images are crucial steps in the processing pipeline of modern digital cameras. As only a third of the color information required to produce a digit…
Adaptive Local Neighborhood-based Neural Networks for MR Image Reconstruction from Undersampled Data
Shijun Liang, Anish Lahiri, Saiprasad Ravishankar
Recent medical image reconstruction techniques focus on generating high-quality medical images suitable for clinical use at the lowest possible cost and with the fewest possible ad…
Sparse-view Cone Beam CT Reconstruction using Data-consistent Supervised and Adversarial Learning from Scarce Training Data
Anish Lahiri, Marc Klasky, Jeffrey A. Fessler +1
Reconstruction of CT images from a limited set of projections through an object is important in several applications ranging from medical imaging to industrial settings. As the num…
Blind Primed Supervised (BLIPS) Learning for MR Image Reconstruction
Anish Lahiri, Guanhua Wang, Saiprasad Ravishankar +1
This paper examines a combined supervised-unsupervised framework involving dictionary-based blind learning and deep supervised learning for MR image reconstruction from under-sampl…
Optimizing MRF-ASL Scan Design for Precise Quantification of Brain Hemodynamics using Neural Network Regression
Anish Lahiri, Jeffrey A Fessler, Luis Hernandez-Garcia
Purpose: Arterial Spin Labeling (ASL) is a quantitative, non-invasive alternative to perfusion imaging with contrast agents. Fixing values of certain model parameters in traditiona…