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

33 citations · 33 across the 1 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

Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction

Matthew J. Muckley, Bruno Riemenschneider, Alireza Radmanesh +20

Accelerating MRI scans is one of the principal outstanding problems in the MRI research community. Towards this goal, we hosted the second fastMRI competition targeted towards reco…

eess.IV2020

End-to-End Variational Networks for Accelerated MRI Reconstruction

Anuroop Sriram, Jure Zbontar, Tullie Murrell +5

The slow acquisition speed of magnetic resonance imaging (MRI) has led to the development of two complementary methods: acquiring multiple views of the anatomy simultaneously (para…

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…

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…