Paper Info
Title
Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge
Abstract
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 owever, one of the major limitations is that the learning-based methods may suffer from the multi-site ...
Year
DOI
Venue
2021
10.1109/TMI.2021.3055428
IEEE Transactions on Medical Imaging
Keywords
DocType
Volume
Image segmentation,Testing,Training,Manuals,Magnetic resonance imaging,Pediatrics,Brain
Journal
40
Issue
ISSN
Citations 
5
0278-0062
2
PageRank 
References 
Authors
0.38
25
33
Name
Order
Citations
PageRank
Yue Sun153.13
Kun Gao24016.56
Zhengwang Wu36016.97
Zhihao Lei420.38
Ying Wei5176.91
Jun Ma61210.74
Xiaoping Yang7155.39
Xue Feng822.07
Li Zhao922832.89
Trung Le Phan1020.38
Jitae Shin1130443.50
Tao Zhong1262.48
Yu Zhang1341.45
Lequan Yu1470639.80
Caizi Li1531.76
Ramesh Basnet1620.38
M. Omair Ahmad1721.05
M. N. S. Swamy181037135.52
Wenao Ma1920.38
Qi Dou2083757.52
Toan Bui2194.57
Camilo Bermudez Noguera2220.38
Bennett Landman2320.38
Ian H. Gotlib24667.47
Kathryn L. Humphreys2520.38
Sarah Shultz2620.38
Longchuan Li2720.38
Sijie Niu2821.39
Weili Lin2915632.78
Valerie Jewells3020.38
Gang Li3138627.90
Dinggang Shen327837611.27
Li Wang33105178.25