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20232026
most citedSegRap2023: A Benchmark of Organs-at-Risk and Gross Tumor Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma

10 citations · 13 across the 15 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024

Meta Curvature-Aware Minimization for Domain Generalization

Ziyang Chen, Yiwen Ye, Feilong Tang +2

Domain generalization (DG) aims to enhance the ability of models trained on source domains to generalize effectively to unseen domains. Recently, Sharpness-Aware Minimization (SAM)…

cs.CV2024

CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation

Yihang Fu, Ziyang Chen, Yiwen Ye +3

Medical images often exhibit distribution shifts due to variations in imaging protocols and scanners across different medical centers. Domain Generalization (DG) methods aim to tra…

cs.CV2024★ 1 cited

MedUniSeg: 2D and 3D Medical Image Segmentation via a Prompt-driven Universal Model

Yiwen Ye, Ziyang Chen, Jianpeng Zhang +2

Universal segmentation models offer significant potential in addressing a wide range of tasks by effectively leveraging discrete annotations. As the scope of tasks and modalities e…

cs.CV2024

Day-Night Adaptation: An Innovative Source-free Adaptation Framework for Medical Image Segmentation

Ziyang Chen, Yiwen Ye, Yongsheng Pan +3

Distribution shifts widely exist in medical images acquired from different medical centres, hindering the deployment of semantic segmentation models trained on one centre (source d…

cs.CV2024

Pre-training Everywhere: Parameter-Efficient Fine-Tuning for Medical Image Analysis via Target Parameter Pre-training

Xingliang Lei, Yiwen Ye, Zhisong Wang +5

Parameter-efficient fine-tuning (PEFT) techniques have emerged to address overfitting and high computational costs associated with fully fine-tuning in self-supervised learning. Ma…

cs.CV2024

From Few to More: Scribble-based Medical Image Segmentation via Masked Context Modeling and Continuous Pseudo Labels

Zhisong Wang, Yiwen Ye, Ziyang Chen +3

Scribble-based weakly supervised segmentation methods have shown promising results in medical image segmentation, significantly reducing annotation costs. However, existing approac…

cs.CV2024

Gradient Alignment Improves Test-Time Adaptation for Medical Image Segmentation

Ziyang Chen, Yiwen Ye, Yongsheng Pan +1

Although recent years have witnessed significant advancements in medical image segmentation, the pervasive issue of domain shift among medical images from diverse centres hinders t…