DyNo: Dynamic Normalization based Test-Time Adaptation for 2D Medical Image Segmentation

Yihang Fu, Ziyang Chen, Yiwen Ye, Yong Xia

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Medical images often exhibit domain shifts owing to varying imaging protocols and scanners across different medical centres. To address this issue, Test-Time Adaptation (TTA) enables pre-trained models to adapt to test samples during inference. In this paper, we propose a novel method, termed Dynamic Normalization (DyNo), for medical image segmentation. Composed of two components, DyNo successfully alleviates domain shifts by adaptively mixing the statistics of multiple domains. We first demonstrated the feasibility of statistics-based methods which merge source and test statistics simply through a supervised toy experiment. Then, we introduce a synthetic domain that synthesizes the distribution information from both the source and target domains using moving average, thereby gradually bridging large domain shifts through the statistics of our synthetic domain. Next, we propose an adaptive fusion strategy, enabling our model to adapt to dynamically changing test data by estimating domain shifts in a fully hyperparameter-free manner. Our DyNo outperforms six competing TTA methods on two benchmark medical image segmentation tasks with multiple scenarios. Extensive ablation studies also demonstrate the effectiveness of synthetic statistics and our adaptive fusion strategy. The code and weights of pre-trained source models are available at https://github.com/Yihang-Fu/DyNo.

源语言英语
主期刊名Machine Learning in Medical Imaging - 15th International Workshop, MLMI 2024, Held in Conjunction with MICCAI 2024, Proceedings
编辑Xuanang Xu, Zhiming Cui, Kaicong Sun, Islem Rekik, Xi Ouyang
出版商Springer Science and Business Media Deutschland GmbH
269-279
页数11
ISBN(印刷版)9783031732836
DOI
出版状态已出版 - 2025
活动15th International Workshop on Machine Learning in Medical Imaging, MLMI 2024 was held in conjunction with the 27th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024 - Marrakesh, 摩洛哥
期限: 6 10月 20246 10月 2024

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
15241 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议15th International Workshop on Machine Learning in Medical Imaging, MLMI 2024 was held in conjunction with the 27th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024
国家/地区摩洛哥
Marrakesh
时期6/10/246/10/24

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