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20182022
most citedForecasting Human Trajectory from Scene History

13 citations · 60 across the 17 of their papers we have counts for

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Showing eess.IVShow all

8 papers · 1 filter

eess.IV20227 cited

JoJoNet: Joint-contrast and Joint-sampling-and-reconstruction Network for Multi-contrast MRI

Lin Zhao, Xiao Chen, Eric Z. Chen +4

Multi-contrast Magnetic Resonance Imaging (MRI) generates multiple medical images with rich and complementary information for routine clinical use; however, it suffers from a long…

eess.IV20211 cited

Accelerating 3D MULTIPLEX MRI Reconstruction with Deep Learning

Eric Z. Chen, Yongquan Ye, Xiao Chen +6

Multi-contrast MRI images provide complementary contrast information about the characteristics of anatomical structures and are commonly used in clinical practice. Recently, a mult…

eess.IV2021

Cardiac Functional Analysis with Cine MRI via Deep Learning Reconstruction

Eric Z. Chen, Xiao Chen, Jingyuan Lyu +7

Retrospectively gated cine (retro-cine) MRI is the clinical standard for cardiac functional analysis. Deep learning (DL) based methods have been proposed for the reconstruction of…

eess.IV2020

Measure Anatomical Thickness from Cardiac MRI with Deep Neural Networks

Qiaoying Huang, Eric Z. Chen, Hanchao Yu +4

Accurate estimation of shape thickness from medical images is crucial in clinical applications. For example, the thickness of myocardium is one of the key to cardiac disease diagno…

eess.IV20205 cited

Real-Time Cardiac Cine MRI with Residual Convolutional Recurrent Neural Network

Eric Z. Chen, Xiao Chen, Jingyuan Lyu +4

Real-time cardiac cine MRI does not require ECG gating in the data acquisition and is more useful for patients who can not hold their breaths or have abnormal heart rhythms. Howeve…

eess.IV20202 cited

Anatomy-Aware Cardiac Motion Estimation

Pingjun Chen, Xiao Chen, Eric Z. Chen +3

Cardiac motion estimation is critical to the assessment of cardiac function. Myocardium feature tracking (FT) can directly estimate cardiac motion from cine MRI, which requires no…