activity
20192022
most citedMSU-Net: Multiscale Statistical U-Net for Real-time 3D Cardiac MRI Video Segmentation

14 citations · 51 across the 18 of their papers we have counts for

collaborators

18 papers

eess.IV2022★ 1 cited

ImageCAS: A Large-Scale Dataset and Benchmark for Coronary Artery Segmentation based on Computed Tomography Angiography Images

An Zeng, Chunbiao Wu, Meiping Huang +10

Cardiovascular disease (CVD) accounts for about half of non-communicable diseases. Vessel stenosis in the coronary artery is considered to be the major risk of CVD. Computed tomogr…

eess.IV2021

"One-Shot" Reduction of Additive Artifacts in Medical Images

Yu-Jen Chen, Yen-Jung Chang, Shao-Cheng Wen +6

Medical images may contain various types of artifacts with different patterns and mixtures, which depend on many factors such as scan setting, machine condition, patients' characte…

eess.IV2021

Hardware-aware Real-time Myocardial Segmentation Quality Control in Contrast Echocardiography

Dewen Zeng, Yukun Ding, Haiyun Yuan +5

Automatic myocardial segmentation of contrast echocardiography has shown great potential in the quantification of myocardial perfusion parameters. Segmentation quality control is a…

eess.IV2021★ 3 cited

ImageTBAD: A 3D Computed Tomography Angiography Image Dataset for Automatic Segmentation of Type-B Aortic Dissection

Zeyang Yao, Jiawei Zhang, Hailong Qiu +6

Type-B Aortic Dissection (TBAD) is one of the most serious cardiovascular events characterized by a growing yearly incidence,and the severity of disease prognosis. Currently, compu…

cs.CV2021

Segmentation with Multiple Acceptable Annotations: A Case Study of Myocardial Segmentation in Contrast Echocardiography

Dewen Zeng, Mingqi Li, Yukun Ding +7

Most existing deep learning-based frameworks for image segmentation assume that a unique ground truth is known and can be used for performance evaluation. This is true for many app…

cs.CV2021★ 6 cited

Positional Contrastive Learning for Volumetric Medical Image Segmentation

Dewen Zeng, Yawen Wu, Xinrong Hu +6

The success of deep learning heavily depends on the availability of large labeled training sets. However, it is hard to get large labeled datasets in medical image domain because o…

eess.IV2021

EchoCP: An Echocardiography Dataset in Contrast Transthoracic Echocardiography for Patent Foramen Ovale Diagnosis

Tianchen Wang, Zhihe Li, Meiping Huang +6

Patent foramen ovale (PFO) is a potential separation between the septum, primum and septum secundum located in the anterosuperior portion of the atrial septum. PFO is one of the ma…

eess.IV2021

Multi-Cycle-Consistent Adversarial Networks for Edge Denoising of Computed Tomography Images

Xiaowe Xu, Jiawei Zhang, Jinglan Liu +10

As one of the most commonly ordered imaging tests, computed tomography (CT) scan comes with inevitable radiation exposure that increases the cancer risk to patients. However, CT im…

cs.CV2021★ 4 cited

Quantization of Deep Neural Networks for Accurate Edge Computing

Wentao Chen, Hailong Qiu, Jian Zhuang +7

Deep neural networks (DNNs) have demonstrated their great potential in recent years, exceeding the per-formance of human experts in a wide range of applications. Due to their large…

eess.IV2021★ 1 cited

ImageCHD: A 3D Computed Tomography Image Dataset for Classification of Congenital Heart Disease

Xiaowei Xu, Tianchen Wang, Jian Zhuang +6

Congenital heart disease (CHD) is the most common type of birth defect, which occurs 1 in every 110 births in the United States. CHD usually comes with severe variations in heart s…

eess.IV2020★ 9 cited

Myocardial Segmentation of Cardiac MRI Sequences with Temporal Consistency for Coronary Artery Disease Diagnosis

Yutian Chen, Xiaowei Xu, Dewen Zeng +6

Coronary artery disease (CAD) is the most common cause of death globally, and its diagnosis is usually based on manual myocardial segmentation of Magnetic Resonance Imaging (MRI) s…

eess.IV2020★ 1 cited

Do Noises Bother Human and Neural Networks In the Same Way? A Medical Image Analysis Perspective

Shao-Cheng Wen, Yu-Jen Chen, Zihao Liu +7

Deep learning had already demonstrated its power in medical images, including denoising, classification, segmentation, etc. All these applications are proposed to automatically ana…

eess.IV2020★ 1 cited

Towards Cardiac Intervention Assistance: Hardware-aware Neural Architecture Exploration for Real-Time 3D Cardiac Cine MRI Segmentation

Dewen Zeng, Weiwen Jiang, Tianchen Wang +6

Real-time cardiac magnetic resonance imaging (MRI) plays an increasingly important role in guiding various cardiac interventions. In order to provide better visual assistance, the…

eess.IV2020

ICA-UNet: ICA Inspired Statistical UNet for Real-time 3D Cardiac Cine MRI Segmentation

Tianchen Wang, Xiaowei Xu, Jinjun Xiong +5

Real-time cine magnetic resonance imaging (MRI) plays an increasingly important role in various cardiac interventions. In order to enable fast and accurate visual assistance, the t…

eess.IV2020

Multi-Cycle-Consistent Adversarial Networks for CT Image Denoising

Jinglan Liu, Yukun Ding, Jinjun Xiong +6

CT image denoising can be treated as an image-to-image translation task where the goal is to learn the transform between a source domain (noisy images) and a target domain …

eess.IV2019★ 14 cited

MSU-Net: Multiscale Statistical U-Net for Real-time 3D Cardiac MRI Video Segmentation

Tianchen Wang, Jinjun Xiong, Xiaowei Xu +5

Cardiac magnetic resonance imaging (MRI) is an essential tool for MRI-guided surgery and real-time intervention. The MRI videos are expected to be segmented on-the-fly in real prac…

eess.IV2019

Accurate Congenital Heart Disease Model Generation for 3D Printing

Xiaowei Xu, Tianchen Wang, Dewen Zeng +5

3D printing has been widely adopted for clinical decision making and interventional planning of Congenital heart disease (CHD), while whole heart and great vessel segmentation is t…

cs.CV2019★ 11 cited

Machine Vision Guided 3D Medical Image Compression for Efficient Transmission and Accurate Segmentation in the Clouds

Zihao Liu, Xiaowei Xu, Tao Liu +7

Cloud based medical image analysis has become popular recently due to the high computation complexities of various deep neural network (DNN) based frameworks and the increasingly l…