8 citations · 12 across the 4 of their papers we have counts for
5 papers
Domain Generalization on Medical Imaging Classification using Episodic Training with Task Augmentation
Chenxin Li, Qi Qi, Xinghao Ding +3
Medical imaging datasets usually exhibit domain shift due to the variations of scanner vendors, imaging protocols, etc. This raises the concern about the generalization capacity of…
Hierarchical Deep Network with Uncertainty-aware Semi-supervised Learning for Vessel Segmentation
Chenxin Li, Wenao Ma, Liyan Sun +4
The analysis of organ vessels is essential for computer-aided diagnosis and surgical planning. But it is not a easy task since the fine-detailed connected regions of organ vessel b…
Unsupervised Anomaly Segmentation using Image-Semantic Cycle Translation
Chenxin Li, Yunlong Zhang, Jiongcheng Li +2
The goal of unsupervised anomaly segmentation (UAS) is to detect the pixel-level anomalies unseen during training. It is a promising field in the medical imaging community, e.g, we…
Consistent Posterior Distributions under Vessel-Mixing: A Regularization for Cross-Domain Retinal Artery/Vein Classification
Chenxin Li, Yunlong Zhang, Zhehan Liang +3
Retinal artery/vein (A/V) classification is a critical technique for diagnosing diabetes and cardiovascular diseases. Although deep learning based methods achieve impressive result…
Few-shot Medical Image Segmentation using a Global Correlation Network with Discriminative Embedding
Liyan Sun, Chenxin Li, Xinghao Ding +3
Despite deep convolutional neural networks achieved impressive progress in medical image computing and analysis, its paradigm of supervised learning demands a large number of annot…