6 citations · 10 across the 7 of their papers we have counts for
9 papers
"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…
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…
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…
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…
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…
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…