173 citations · 272 across the 12 of their papers we have counts for
12 papers
3D Matting: A Benchmark Study on Soft Segmentation Method for Pulmonary Nodules Applied in Computed Tomography
Lin Wang, Xiufen Ye, Donghao Zhang +9
Usually, lesions are not isolated but are associated with the surrounding tissues. For example, the growth of a tumour can depend on or infiltrate into the surrounding tissues. Due…
3D Matting: A Soft Segmentation Method Applied in Computed Tomography
Lin Wang, Xiufen Ye, Donghao Zhang +7
Three-dimensional (3D) images, such as CT, MRI, and PET, are common in medical imaging applications and important in clinical diagnosis. Semantic ambiguity is a typical feature of…
Camera Adaptation for Fundus-Image-Based CVD Risk Estimation
Zhihong Lin, Danli Shi, Donghao Zhang +3
Recent studies have validated the association between cardiovascular disease (CVD) risk and retinal fundus images. Combining deep learning (DL) and portable fundus cameras will ena…
Medical Visual Question Answering: A Survey
Zhihong Lin, Donghao Zhang, Qingyi Tao +5
Medical Visual Question Answering~(VQA) is a combination of medical artificial intelligence and popular VQA challenges. Given a medical image and a clinically relevant question in…
Mutual Consistency Learning for Semi-supervised Medical Image Segmentation
Yicheng Wu, Zongyuan Ge, Donghao Zhang +4
In this paper, we propose a novel mutual consistency network (MC-Net+) to effectively exploit the unlabeled data for semi-supervised medical image segmentation. The MC-Net+ model i…
Medical Matting: A New Perspective on Medical Segmentation with Uncertainty
Lin Wang, Lie Ju, Xin Wang +8
It is difficult to accurately label ambiguous and complex shaped targets manually by binary masks. The weakness of binary mask under-expression is highlighted in medical image segm…
Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting
Dongnan Liu, Donghao Zhang, Yang Song +5
Unsupervised domain adaptation (UDA) for nuclei instance segmentation is important for digital pathology, as it alleviates the burden of labor-intensive annotation and domain shift…
Graph Attention Network based Pruning for Reconstructing 3D Liver Vessel Morphology from Contrasted CT Images
Donghao Zhang, Siqi Liu, Shikha Chaganti +5
With the injection of contrast material into blood vessels, multi-phase contrasted CT images can enhance the visibility of vessel networks in the human body. Reconstructing the 3D…
Panoptic Feature Fusion Net: A Novel Instance Segmentation Paradigm for Biomedical and Biological Images
Dongnan Liu, Donghao Zhang, Yang Song +2
Instance segmentation is an important task for biomedical and biological image analysis. Due to the complicated background components, the high variability of object appearances, n…
Region and Object based Panoptic Image Synthesis through Conditional GANs
Heng Wang, Donghao Zhang, Yang Song +3
Image-to-image translation is significant to many computer vision and machine learning tasks such as image synthesis and video synthesis. It has primary applications in the graphic…
3D Global Convolutional Adversarial Network\\ for Prostate MR Volume Segmentation
Haozhe Jia, Yang Song, Donghao Zhang +5
Advanced deep learning methods have been developed to conduct prostate MR volume segmentation in either a 2D or 3D fully convolutional manner. However, 2D methods tend to have limi…
Review of Strong Field Approximation and Investigating Semiclassical Evolution Approach
Renjing Xu, Donghao Zhang, Anatoli Kheifets +1
This paper theoretically analyzes the behavior of an atom driven by a strong electro-magnetic field. Moreover, besides traditional quantum mechanics method, we also investigate sem…