45 citations · 186 across the 19 of their papers we have counts for
20 papers
A new method using deep transfer learning on ECG to predict the response to cardiac resynchronization therapy
Zhuo He, Hongjin Si, Xinwei Zhang +3
Background: Cardiac resynchronization therapy (CRT) has emerged as an effective treatment for heart failure patients with electrical dyssynchrony. However, accurately predicting wh…
Coronary Artery Semantic Labeling using Edge Attention Graph Matching Network
Chen Zhao, Zhihui Xu, Guang-Uei Hung +1
Coronary artery disease (CAD) is one of the primary causes leading deaths worldwide. The presence of atherosclerotic lesions in coronary arteries is the underlying pathophysiologic…
A new method using deep learning to predict the response to cardiac resynchronization therapy
Kristoffer Larsena, Zhuo He, Chen Zhao +8
Background. Clinical parameters measured from gated single-photon emission computed tomography myocardial perfusion imaging (SPECT MPI) have value in predicting cardiac resynchroni…
CLCLSA: Cross-omics Linked embedding with Contrastive Learning and Self Attention for multi-omics integration with incomplete multi-omics data
Chen Zhao, Anqi Liu, Xiao Zhang +6
Integration of heterogeneous and high-dimensional multi-omics data is becoming increasingly important in understanding genetic data. Each omics technique only provides a limited vi…
AGMN: Association Graph-based Graph Matching Network for Coronary Artery Semantic Labeling on Invasive Coronary Angiograms
Chen Zhao, Zhihui Xu, Jingfeng Jiang +4
Semantic labeling of coronary arterial segments in invasive coronary angiography (ICA) is important for automated assessment and report generation of coronary artery stenosis in th…
Incremental Value and Interpretability of Radiomics Features of Both Lung and Epicardial Adipose Tissue for Detecting the Severity of COVID-19 Infection
Ni Yao, Yanhui Tian, Daniel Gama das Neves +9
Epicardial adipose tissue (EAT) is known for its pro-inflammatory properties and association with Coronavirus Disease 2019 (COVID-19) severity. However, current EAT segmentation me…
A New Hip Fracture Risk Index Derived from FEA-Computed Proximal Femur Fracture Loads and Energies-to-Failure
Xuewei Cao, Joyce H Keyak, Sigurdur Sigurdsson +7
Hip fracture risk assessment is an important but challenging task. Quantitative CT-based patient specific finite element analysis (FEA) computes the force (fracture load) to break…
A new method using machine learning to integrate ECG and gated SPECT MPI for Cardiac Resynchronization Therapy Decision Support on behalf of the VISION-CRT
Fernando de A. Fernandes, Kristoffer Larsen, Zhuo He +7
Cardiac resynchronization therapy (CRT) has been established as an important therapy for heart failure. Mechanical dyssynchrony has the potential to predict responders to CRT. The…
Multi-view information fusion using multi-view variational autoencoders to predict proximal femoral strength
Chen Zhao, Joyce H Keyak, Xuewei Cao +10
The aim of this paper is to design a deep learning-based model to predict proximal femoral strength using multi-view information fusion. Method: We developed new models using multi…
Automatic reorientation by deep learning to generate short axis SPECT myocardial perfusion images
Fubao Zhu, Guojie Wang, Chen Zhao +6
Single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) can be displayed both in traditional short-axis (SA) cardiac planes and polar maps for interpre…
Automatic extraction of coronary arteries using deep learning in invasive coronary angiograms
Yinghui Meng, Zhenglong Du, Chen Zhao +4
Accurate extraction of coronary arteries from invasive coronary angiography (ICA) is important in clinical decision-making for the diagnosis and risk stratification of coronary art…
A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images
Fubao Zhu, Jinyu Zhao, Chen Zhao +8
Background: The assessment of left ventricular (LV) function by myocardial perfusion SPECT (MPS) relies on accurate myocardial segmentation. The purpose of this paper is to develop…
Spatial-temporal V-Net for automatic segmentation and quantification of right ventricles in gated myocardial perfusion SPECT images
Chen Zhao, Shi Shi, Zhuo He +5
Background. Functional assessment of right ventricle (RV) using gated myocardial perfusion single-photon emission computed tomography (MPS) heavily relies on the precise extraction…
A method using deep learning to discover new predictors of CRT response from mechanical dyssynchrony on gated SPECT MPI
Zhuo He, Xinwei Zhang, Chen Zhao +5
Background. Studies have shown that the conventional left ventricular mechanical dyssynchrony (LVMD) parameters have their own statistical limitations. The purpose of this study is…
A Deep Learning-based Method to Extract Lumen and Media-Adventitia in Intravascular Ultrasound Images
Fubao Zhu, Zhengyuan Gao, Chen Zhao +5
Intravascular ultrasound (IVUS) imaging allows direct visualization of the coronary vessel wall and is suitable for the assessment of atherosclerosis and the degree of stenosis. Ac…
A Deep Learning-Based Approach to Extracting Periosteal and Endosteal Contours of Proximal Femur in Quantitative CT Images
Yu Deng, Ling Wang, Chen Zhao +4
Automatic CT segmentation of proximal femur is crucial for the diagnosis and risk stratification of orthopedic diseases; however, current methods for the femur CT segmentation main…
A new approach to extracting coronary arteries and detecting stenosis in invasive coronary angiograms
Chen Zhao, Haipeng Tang, Daniel McGonigle +6
In stable coronary artery disease (CAD), reduction in mortality and/or myocardial infarction with revascularization over medical therapy has not been reliably achieved. Coronary ar…
Semantic Segmentation Using Deep Learning to Extract Total Extraocular Muscles and Optic Nerve from Orbital Computed Tomography Images
Fubao Zhu, Zhengyuan Gao, Chen Zhao +7
Objectives: Precise segmentation of total extraocular muscles (EOM) and optic nerve (ON) is essential to assess anatomical development and progression of thyroid-associated ophthal…
A Deep Learning-Based Method for Automatic Segmentation of Proximal Femur from Quantitative Computed Tomography Images
Chen Zhao, Joyce H. Keyak, Jinshan Tang +10
Purpose: Proximal femur image analyses based on quantitative computed tomography (QCT) provide a method to quantify the bone density and evaluate osteoporosis and risk of fracture.…
3D Fusion between Fluoroscopy Angiograms and SPECT Myocardial Perfusion Images to Guide Percutaneous Coronary Intervention
Haipeng Tang, Robert R. Bober, Chen Zhao +5
Background. Percutaneous coronary intervention(PCI) in stable coronary artery disease(CAD) is commonly triggered by abnormal myocardial perfusion imaging(MPI). However, due to the…