2.2k citations · 4.4k across the 41 of their papers we have counts for
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Fast Learning-based Registration of Sparse 3D Clinical Images
Kathleen M. Lewis, Natalia S. Rost, John Guttag +1
We introduce SparseVM, a method that registers clinical-quality 3D MR scans both faster and more accurately than previously possible. Deformable alignment, or registration, of clin…
Multiple Instance Learning for ECG Risk Stratification
Divya Shanmugam, Davis Blalock, John Guttag
Patients who suffer an acute coronary syndrome are at elevated risk for adverse cardiovascular events such as myocardial infarction and cardiovascular death. Accurate assessment of…
VoxelMorph: A Learning Framework for Deformable Medical Image Registration
Guha Balakrishnan, Amy Zhao, Mert R. Sabuncu +2
We present VoxelMorph, a fast learning-based framework for deformable, pairwise medical image registration. Traditional registration methods optimize an objective function for each…
Sprintz: Time Series Compression for the Internet of Things
Davis Blalock, Samuel Madden, John Guttag
Thanks to the rapid proliferation of connected devices, sensor-generated time series constitute a large and growing portion of the world's data. Often, this data is collected from…
Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICU
Harini Suresh, Jen J. Gong, John Guttag
Machine learning approaches have been effective in predicting adverse outcomes in different clinical settings. These models are often developed and evaluated on datasets with heter…
Visualizing Patient Timelines in the Intensive Care Unit
Dina Levy-Lambert, Jen J. Gong, Tristan Naumann +2
Electronic Health Records (EHRs) contain a large volume of heterogeneous patient data, which are useful at the point of care and for retrospective research. These data are typicall…
Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration
Adrian V. Dalca, Guha Balakrishnan, John Guttag +1
Traditional deformable registration techniques achieve impressive results and offer a rigorous theoretical treatment, but are computationally intensive since they solve an optimiza…
Synthesizing Images of Humans in Unseen Poses
Guha Balakrishnan, Amy Zhao, Adrian V. Dalca +2
We address the computational problem of novel human pose synthesis. Given an image of a person and a desired pose, we produce a depiction of that person in that pose, retaining the…
An Unsupervised Learning Model for Deformable Medical Image Registration
Guha Balakrishnan, Amy Zhao, Mert R. Sabuncu +2
We present a fast learning-based algorithm for deformable, pairwise 3D medical image registration. Current registration methods optimize an objective function independently for eac…