130 citations · 212 across the 36 of their papers we have counts for
8 papers · 1 filter
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…
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…
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…
Towards Visually Explaining Similarity Models
Meng Zheng, Srikrishna Karanam, Terrence Chen +2
We consider the problem of visually explaining similarity models, i.e., explaining why a model predicts two images to be similar in addition to producing a scalar score. While much…
Motion Pyramid Networks for Accurate and Efficient Cardiac Motion Estimation
Hanchao Yu, Xiao Chen, Humphrey Shi +3
Cardiac motion estimation plays a key role in MRI cardiac feature tracking and function assessment such as myocardium strain. In this paper, we propose Motion Pyramid Networks, a n…
MRI Image Reconstruction via Learning Optimization Using Neural ODEs
Eric Z. Chen, Terrence Chen, Shanhui Sun
We propose to formulate MRI image reconstruction as an optimization problem and model the optimization trajectory as a dynamic process using ordinary differential equations (ODEs).…
FOAL: Fast Online Adaptive Learning for Cardiac Motion Estimation
Hanchao Yu, Shanhui Sun, Haichao Yu +4
Motion estimation of cardiac MRI videos is crucial for the evaluation of human heart anatomy and function. Recent researches show promising results with deep learning-based methods…
Hierarchical Kinematic Human Mesh Recovery
Georgios Georgakis, Ren Li, Srikrishna Karanam +3
We consider the problem of estimating a parametric model of 3D human mesh from a single image. While there has been substantial recent progress in this area with direct regression…