Improving diagnosis accuracy of brain volume abnormalities during childhood with an automated MP2RAGE-based MRI brain segmentation

Author(s):  
Maxence Serru ◽  
Bénédicte Marechal ◽  
Tobias Kober ◽  
Leo Ribier ◽  
Catherine Sembely Taveau ◽  
...  
Author(s):  
Deborah Sturm ◽  
Philip Koshy ◽  
Diana Kovalerchik ◽  
Nirav Thakkar

2018 ◽  
Vol 28 (4) ◽  
pp. 399-405 ◽  
Author(s):  
Robert Zivadinov ◽  
Jennie Medin ◽  
Nasreen Khan ◽  
Jonathan R. Korn ◽  
Niels Bergsland ◽  
...  

2017 ◽  
Vol 10 (02) ◽  
pp. 1750026 ◽  
Author(s):  
Yang Zhang ◽  
Shufan Ye ◽  
Weifeng Ding

A new method of MRI brain segmentation integrates fuzzy [Formula: see text]-means (FCM) clustering and rough set theory. In this paper, we use rough set algorithm to find the suitable initial clustering number to initial clustering centers for FCM. Then we use FCM to MRI brain segmentation, but the algorithm of FCM has the limitation of converging to local infinitesimal point in medical segmentation. While avoiding being trapped in a local optimum, we use the particle swarm optimization algorithm to restrict convergence of FCM which can reduce calculation. The final experiment results show that improved algorithm not only retains the advantages of rapid convergence but also can control the local convergence and improve the global search ability. The method in this paper is better than that of cluttering performance.


2006 ◽  
Vol 24 (10) ◽  
pp. 1065-1079 ◽  
Author(s):  
M. Ibrahim ◽  
N. John ◽  
M. Kabuka ◽  
A. Younis

2018 ◽  
Vol 278 ◽  
pp. 69-76 ◽  
Author(s):  
David E. Ross ◽  
Alfred L. Ochs ◽  
David F. Tate ◽  
Umit Tokac ◽  
John Seabaugh ◽  
...  

2015 ◽  
Vol 256 ◽  
pp. 808-818 ◽  
Author(s):  
Ali Ahmadvand ◽  
Mohammad Reza Daliri
Keyword(s):  

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