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20182024
most citedClass-Aware Adversarial Transformers for Medical Image Segmentation

78 citations · 247 across the 17 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

eess.IV2022★ 22 cited

Mine yOur owN Anatomy: Revisiting Medical Image Segmentation with Extremely Limited Labels

Chenyu You, Weicheng Dai, Fenglin Liu +6

Recent studies on contrastive learning have achieved remarkable performance solely by leveraging few labels in the context of medical image segmentation. Existing methods mainly fo…

eess.IV2022

Learning correspondences of cardiac motion from images using biomechanics-informed modeling

Xiaoran Zhang, Chenyu You, Shawn Ahn +3

Learning spatial-temporal correspondences in cardiac motion from images is important for understanding the underlying dynamics of cardiac anatomical structures. Many methods explic…

cs.CV2022★ 1 cited

Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation

Chenyu You, Jinlin Xiang, Kun Su +5

Many medical datasets have recently been created for medical image segmentation tasks, and it is natural to question whether we can use them to sequentially train a single model th…

cs.CV2022★ 8 cited

Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-aware Contrastive Distillation

Chenyu You, Weicheng Dai, Yifei Min +2

Contrastive learning has shown great promise over annotation scarcity problems in the context of medical image segmentation. Existing approaches typically assume a balanced class d…

cs.CV2022★ 78 cited

Class-Aware Adversarial Transformers for Medical Image Segmentation

Chenyu You, Ruihan Zhao, Fenglin Liu +5

Transformers have made remarkable progress towards modeling long-range dependencies within the medical image analysis domain. However, current transformer-based models suffer from…