Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge

To better understand early brain development in health and disorder, it is critical to accurately segment infant brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). Deep learning-based methods have achieved state-of-the-art performance; h owe...

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Detalhes bibliográficos
Publicado no:IEEE Trans Med Imaging
Main Authors: Sun, Yue, Gao, Kun, Wu, Zhengwang, Li, Guannan, Zong, Xiaopeng, Lei, Zhihao, Wei, Ying, Ma, Jun, Yang, Xiaoping, Feng, Xue, Zhao, Li, Phan, Trung Le, Shin, Jitae, Zhong, Tao, Zhang, Yu, Yu, Lequan, Li, Caizi, Basnet, Ramesh, Ahmad, M. Omair, Swamy, M. N. S., Ma, Wenao, Dou, Qi, Bui, Toan Duc, Noguera, Camilo Bermudez, Landman, Bennett, Gotlib, Ian H., Humphreys, Kathryn L., Shultz, Sarah, Li, Longchuan, Niu, Sijie, Lin, Weili, Jewells, Valerie, Shen, Dinggang, Li, Gang, Wang, Li
Formato: Artigo
Idioma:Inglês
Publicado em: 2021
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC8246057/
https://ncbi.nlm.nih.gov/pubmed/33507867
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TMI.2021.3055428
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