35 citations · 80 across the 15 of their papers we have counts for
16 papers · 1 filter
D-Former: A U-shaped Dilated Transformer for 3D Medical Image Segmentation
Yixuan Wu, Kuanlun Liao, Jintai Chen +4
Computer-aided medical image segmentation has been applied widely in diagnosis and treatment to obtain clinically useful information of shapes and volumes of target organs and tiss…
Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation
Hao Zheng, Jun Han, Hongxiao Wang +4
A large labeled dataset is a key to the success of supervised deep learning, but for medical image segmentation, it is highly challenging to obtain sufficient annotated images for…
Objective-Dependent Uncertainty Driven Retinal Vessel Segmentation
Suraj Mishra, Danny Z. Chen, X. Sharon Hu
From diagnosing neovascular diseases to detecting white matter lesions, accurate tiny vessel segmentation in fundus images is critical. Promising results for accurate vessel segmen…
Flow-Mixup: Classifying Multi-labeled Medical Images with Corrupted Labels
Jintai Chen, Hongyun Yu, Ruiwei Feng +2
In clinical practice, medical image interpretation often involves multi-labeled classification, since the affected parts of a patient tend to present multiple symptoms or comorbidi…
Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation
Hongxiao Wang, Hao Zheng, Jianxu Chen +3
Automatic histopathology image segmentation is crucial to disease analysis. Limited available labeled data hinders the generalizability of trained models under the fully supervised…
Globally Optimal Segmentation of Mutually Interacting Surfaces using Deep Learning
Hui Xie, Zhe Pan, Leixin Zhou +5
Segmentation of multiple surfaces in medical images is a challenging problem, further complicated by the frequent presence of weak boundary and mutual influence between adjacent ob…