Zobrazeno 1 - 10
of 541
pro vyhledávání: '"Lai, Yuen"'
Autor:
Kenneth Ka Hei Lai, Fatema Mohamed Ali Abdulla Aljufairi, Jake Uy Sebastian, Yingying Wei, Ruofan Jia, Karen Kar Wun Chan, Elaine Yuen Ling Au, Alan Chun Hong Lee, Chiu Ming Ng, Hunter Kwok Lai Yuen, Wilson Wai Kuen Yip, Alvin Lerrmann Young, George Pak Man Cheng, Clement Chee Yung Tham, Chi Pui Pang, Kelvin Kam Lung Chong
Publikováno v:
European Thyroid Journal, Vol 13, Iss 4, Pp 1-7 (2024)
Purpose: This study aims to report correlations between thyroid-stimulating immunoglobulin (TSI) and both clinical and radiological parameters in recent-onset symptomatic thyroid eye disease (TED) patients. Methods: A prospective cohort study of TED
Externí odkaz:
https://doaj.org/article/e5f299d026af4b30969fbf98ab295f58
Publikováno v:
Digital Health, Vol 10 (2024)
Objective Convolutional neural networks (CNNs) have achieved state-of-the-art results in various medical image segmentation tasks. However, CNNs often assume that the source and target dataset follow the same probability distribution and when this as
Externí odkaz:
https://doaj.org/article/7764ad981e024174a4879f10e4849a53
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
Deep learning models have obtained state-of-the-art results for medical image analysis. However, when these models are tested on an unseen domain there is a significant performance degradation. In this work, we present an unsupervised Cross-Modality
Externí odkaz:
http://arxiv.org/abs/2110.15823
Autor:
Baldeon-Calisto, Maria, Rivera-Velastegui, Francisco, Lai-Yuen, Susana K., Riofrío, Daniel, Pérez-Pérez, Noel, Benítez, Diego, Flores-Moyano, Ricardo
Publikováno v:
In Computers in Biology and Medicine July 2024 177
Deep learning methods have become very successful at solving many complex tasks such as image classification and segmentation, speech recognition and machine translation. Nevertheless, manually designing a neural network for a specific problem is ver
Externí odkaz:
http://arxiv.org/abs/2011.04463
Publikováno v:
In Neurocomputing 1 December 2023 560
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Fang, Christian, Shen, Wan Yiu, Wong, Janus Siu Him, Yee, Dennis King-Hang, Yung, Colin Shing-Yat, Fang, Evan, Lai, Yuen Shan, Woo, Siu Bon, Cheung, Jake, Chau, Jackie Yee-Man, Ip, Ka Chun, Li, Wilson, Leung, Frankie
Publikováno v:
In Injury August 2023 54(8)
Segmentation is a critical step in medical image analysis. Fully Convolutional Networks (FCNs) have emerged as powerful segmentation models achieving state-of-the-art results in various medical image datasets. Network architectures are usually design
Externí odkaz:
http://arxiv.org/abs/1907.11587