44 citations · 62 across the 8 of their papers we have counts for
6 papers · 1 filter
Domain Adaptation Meets Zero-Shot Learning: An Annotation-Efficient Approach to Multi-Modality Medical Image Segmentation
Cheng Bian, Chenglang Yuan, Kai Ma +3
Due to the lack of properly annotated medical data, exploring the generalization capability of the deep model is becoming a public concern. Zero-shot learning (ZSL) has emerged in…
Multi-Anchor Active Domain Adaptation for Semantic Segmentation
Munan Ning, Donghuan Lu, Dong Wei +5
Unsupervised domain adaption has proven to be an effective approach for alleviating the intensive workload of manual annotation by aligning the synthetic source-domain data and the…
A New Bidirectional Unsupervised Domain Adaptation Segmentation Framework
Munan Ning, Cheng Bian, Dong Wei +5
Domain shift happens in cross-domain scenarios commonly because of the wide gaps between different domains: when applying a deep learning model well-trained in one domain to anothe…
A Macro-Micro Weakly-supervised Framework for AS-OCT Tissue Segmentation
Munan Ning, Cheng Bian, Donghuan Lu +7
Primary angle closure glaucoma (PACG) is the leading cause of irreversible blindness among Asian people. Early detection of PACG is essential, so as to provide timely treatment and…
AGE Challenge: Angle Closure Glaucoma Evaluation in Anterior Segment Optical Coherence Tomography
Huazhu Fu, Fei Li, Xu Sun +22
Angle closure glaucoma (ACG) is a more aggressive disease than open-angle glaucoma, where the abnormal anatomical structures of the anterior chamber angle (ACA) may cause an elevat…
Identification of primary angle-closure on AS-OCT images with Convolutional Neural Networks
Chenglang Yuan, Cheng Bian, Hongjian Kang +3
Primary angle-closure disease (PACD) is a severe retinal disease, which might cause irreversible vision loss. In clinic, accurate identification of angle-closure and localization o…