3 papers
cs.CV2022
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…
eess.IV2021
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…
eess.IV2019
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…