7 papers
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…
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…
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…
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 …
Revisiting the Evaluation of Uncertainty Estimation and Its Application to Explore Model Complexity-Uncertainty Trade-Off
Yukun Ding, Jinglan Liu, Jinjun Xiong +1
Accurately estimating uncertainties in neural network predictions is of great importance in building trusted DNNs-based models, and there is an increasing interest in providing acc…
PBGen: Partial Binarization of Deconvolution-Based Generators for Edge Intelligence
Jinglan Liu, Jiaxin Zhang, Yukun Ding +3
This work explores the binarization of the deconvolution-based generator in a GAN for memory saving and speedup of image construction. Our study suggests that different from convol…