activity
20192026
most citedDeep Networks to Automatically Detect Late-activating Regions of the Heart

1 citations · 3 across the 15 of their papers we have counts for

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eess.IV2024★ 1 cited

Assessment of Clonal Hematopoiesis of Indeterminate Potential and Future Cardiomyopathy from Cardiac Magnetic Resonance Imaging using Deep Learning in a Cardio-oncology Population

Jiarui Xing, Sangeon Ryu, Shawn Ahn +7

We propose a novel deep learning framework to identify clonal hematopoiesis of indeterminate potential (CHIP), a somatic mutation condition associated with adverse cardiovascular o…

eess.IV2022

Joint Deep Learning for Improved Myocardial Scar Detection from Cardiac MRI

Jiarui Xing, Shuo Wang, Kenneth C. Bilchick +2

Automated identification of myocardial scar from late gadolinium enhancement cardiac magnetic resonance images (LGE-CMR) is limited by image noise and artifacts such as those relat…

eess.IV2022

Multitask Learning for Improved Late Mechanical Activation Detection of Heart from Cine DENSE MRI

Jiarui Xing, Shuo Wang, Kenneth C. Bilchick +3

The selection of an optimal pacing site, which is ideally scar-free and late activated, is critical to the response of cardiac resynchronization therapy (CRT). Despite the success…

eess.IV2020★ 1 cited

Deep Networks to Automatically Detect Late-activating Regions of the Heart

Jiarui Xing, Sona Ghadimi, Mohammad Abdishektaei +3

This paper presents a novel method to automatically identify late-activating regions of the left ventricle from cine Displacement Encoding with Stimulated Echo (DENSE) MR images. W…

eess.IV2019★ 1 cited

Plug-and-Play Priors for Reconstruction-based Placental Image Registration

Jiarui Xing, Ulugbek Kamilov, Wenjie Wu +2

This paper presents a novel deformable registration framework, leveraging an image prior specified through a denoising function, for severely noise-corrupted placental images. Rece…