activity
20222026
most citedCrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation

99 citations · 107 across the 10 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

CardioLens: Revealing the Clinical Reality Gap of MLLMs via Multi-Sequence Cardiac MRI Evaluations

Zixian Su, Hongkai Zhang, Fan Gao +12

Multimodal Large Language Models (MLLMs) have shown strong performance on public medical benchmarks, yet existing evaluations often remain weak proxies for clinical use, relying on…

cs.CV2024

SCMix: Stochastic Compound Mixing for Open Compound Domain Adaptation in Semantic Segmentation

Kai Yao, Zhaorui Tan, Zixian Su +3

Open compound domain adaptation (OCDA) aims to transfer knowledge from a labeled source domain to a mix of unlabeled homogeneous compound target domains while generalizing to open…

cs.CV2023

Unraveling Batch Normalization for Realistic Test-Time Adaptation

Zixian Su, Jingwei Guo, Kai Yao +3

While recent test-time adaptations exhibit efficacy by adjusting batch normalization to narrow domain disparities, their effectiveness diminishes with realistic mini-batches due to…

cs.CV2022★ 8 cited

Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation

Zixian Su, Kai Yao, Xi Yang +3

Single-source domain generalization (SDG) in medical image segmentation is a challenging yet essential task as domain shifts are quite common among clinical image datasets. Previou…

cs.CV2022

Mind The Gap: Alleviating Local Imbalance for Unsupervised Cross-Modality Medical Image Segmentation

Zixian Su, Kai Yao, Xi Yang +4

Unsupervised cross-modality medical image adaptation aims to alleviate the severe domain gap between different imaging modalities without using the target domain label. A key in th…