Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Su, Zixian"'
Medical Image Analysis (MedIA) has become indispensable in modern healthcare, enhancing clinical diagnostics and personalized treatment. Despite the remarkable advancements supported by deep learning (DL) technologies, their practical deployment face
Externí odkaz:
http://arxiv.org/abs/2411.05824
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 unseen domains. Existing OCDA methods solve the intra-domain gaps by a
Externí odkaz:
http://arxiv.org/abs/2405.14278
Whilst spectral Graph Neural Networks (GNNs) are theoretically well-founded in the spectral domain, their practical reliance on polynomial approximation implies a profound linkage to the spatial domain. As previous studies rarely examine spectral GNN
Externí odkaz:
http://arxiv.org/abs/2401.09071
While recent test-time adaptations exhibit efficacy by adjusting batch normalization to narrow domain disparities, their effectiveness diminishes with realistic mini-batches due to inaccurate target estimation. As previous attempts merely introduce s
Externí odkaz:
http://arxiv.org/abs/2312.09486
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. Previous attempts most conduct global-only/random augmentation. Their augment
Externí odkaz:
http://arxiv.org/abs/2211.14805
Mind The Gap: Alleviating Local Imbalance for Unsupervised Cross-Modality Medical Image Segmentation
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 this campaign relies upon aligning the distributions of source and targe
Externí odkaz:
http://arxiv.org/abs/2205.11888
Autor:
Wei, Kerui, Cao, Huatang, Liu, Han, Shepherd, Daniel, Kho, Zhiquan, Su, Zixian, Donoghue, Jack, Martins, João P., Lindley, Matthew, Liu, Xuzhao, Zhong, Xiangli, Eggeman, Alexander, Haigh, Sarah J., Withers, Philip J., Xiao, Ping
Publikováno v:
In Materials & Design September 2024 245
Autor:
Yue, Zengliang, Su, Zixian, Paul, Partha P., Marsh, Alastair T.M., Macente, Alice, Di Michiel, Marco, Provis, John L., Withers, Philip J., Bernal, Susan A.
Publikováno v:
In Cement and Concrete Research January 2025 187
Autor:
Dorent, Reuben, Kujawa, Aaron, Ivory, Marina, Bakas, Spyridon, Rieke, Nicola, Joutard, Samuel, Glocker, Ben, Cardoso, Jorge, Modat, Marc, Batmanghelich, Kayhan, Belkov, Arseniy, Calisto, Maria Baldeon, Choi, Jae Won, Dawant, Benoit M., Dong, Hexin, Escalera, Sergio, Fan, Yubo, Hansen, Lasse, Heinrich, Mattias P., Joshi, Smriti, Kashtanova, Victoriya, Kim, Hyeon Gyu, Kondo, Satoshi, Kruse, Christian N., Lai-Yuen, Susana K., Li, Hao, Liu, Han, Ly, Buntheng, Oguz, Ipek, Shin, Hyungseob, Shirokikh, Boris, Su, Zixian, Wang, Guotai, Wu, Jianghao, Xu, Yanwu, Yao, Kai, Zhang, Li, Ourselin, Sebastien, Shapey, Jonathan, Vercauteren, Tom
Domain Adaptation (DA) has recently raised strong interests in the medical imaging community. While a large variety of DA techniques has been proposed for image segmentation, most of these techniques have been validated either on private datasets or
Externí odkaz:
http://arxiv.org/abs/2201.02831
Autor:
Wei, Kerui, Liu, Han, Cao, Huatang, Kho, Zhiquan, Eggeman, Alexander, Martins, João P., Yilmaz, Esma, Donoghue, Jack, Su, Zixian, Xiao, Ping
Publikováno v:
In Journal of the European Ceramic Society July 2024 44(7):4362-4375