activity
20182021
most citedCOVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction

33 citations · 43 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV202133 cited

COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction

Anuroop Sriram, Matthew Muckley, Koustuv Sinha +7

The rapid spread of COVID-19 cases in recent months has strained hospital resources, making rapid and accurate triage of patients presenting to emergency departments a necessity. M…

eess.IV2020

Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge

Florian Knoll, Tullie Murrell, Anuroop Sriram +8

Purpose: To advance research in the field of machine learning for MR image reconstruction with an open challenge. Methods: We provided participants with a dataset of raw k-space da…

eess.IV2019

Training a Neural Network for Gibbs and Noise Removal in Diffusion MRI

Matthew J. Muckley, Benjamin Ades-Aron, Antonios Papaioannou +7

We develop and evaluate a neural network-based method for Gibbs artifact and noise removal. A convolutional neural network (CNN) was designed for artifact removal in diffusion-weig…

cs.CV201910 cited

Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition

Zizhao Zhang, Adriana Romero, Matthew J. Muckley +3

The goal of MRI reconstruction is to restore a high fidelity image from partially observed measurements. This partial view naturally induces reconstruction uncertainty that can onl…

cs.CV2018

fastMRI: An Open Dataset and Benchmarks for Accelerated MRI

Jure Zbontar, Florian Knoll, Anuroop Sriram +24

Accelerating Magnetic Resonance Imaging (MRI) by taking fewer measurements has the potential to reduce medical costs, minimize stress to patients and make MRI possible in applicati…