15 citations · 29 across the 6 of their papers we have counts for
6 papers
Unsupervised Adaptation of Polyp Segmentation Models via Coarse-to-Fine Self-Supervision
Jiexiang Wang, Chaoqi Chen
Unsupervised Domain Adaptation~(UDA) has attracted a surge of interest over the past decade but is difficult to be used in real-world applications. Considering the privacy-preserva…
Multi-Task Neural Networks with Spatial Activation for Retinal Vessel Segmentation and Artery/Vein Classification
Wenao Ma, Shuang Yu, Kai Ma +3
Retinal artery/vein (A/V) classification plays a critical role in the clinical biomarker study of how various systemic and cardiovascular diseases affect the retinal vessels. Conve…
Cardiac Segmentation on Late Gadolinium Enhancement MRI: A Benchmark Study from Multi-Sequence Cardiac MR Segmentation Challenge
Xiahai Zhuang, Jiahang Xu, Xinzhe Luo +20
Accurate computing, analysis and modeling of the ventricles and myocardium from medical images are important, especially in the diagnosis and treatment management for patients suff…
Multi-sequence Cardiac MR Segmentation with Adversarial Domain Adaptation Network
Jiexiang Wang, Hongyu Huang, Chaoqi Chen +3
Automatic and accurate segmentation of the ventricles and myocardium from multi-sequence cardiac MRI (CMR) is crucial for the diagnosis and treatment management for patients suffer…
Uncertainty-Guided Domain Alignment for Layer Segmentation in OCT Images
Jiexiang Wang, Cheng Bian, Meng Li +6
Automatic and accurate segmentation for retinal and choroidal layers of Optical Coherence Tomography (OCT) is crucial for detection of various ocular diseases. However, because of…
An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection
Liyan Sun, Jiexiang Wang, Yue Huang +3
The identification of lesion within medical image data is necessary for diagnosis, treatment and prognosis. Segmentation and classification approaches are mainly based on supervise…