Spatial normalization of brain images and beyond
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- 作者：J.-F. Mangina ; j ; jfmangin@gmail.com" class="auth_mail" title="E-mail the corresponding author ; J. Lebenberga ; f ; S. Lefranca ; j ; N. Labraa ; G. Auziasb ; M. Labita ; j ; M. Guevarac ; H. Mohlbergd ; P. Rocae ; P. Guevarac ; J. Duboisf ; F. Leroyf ; G. Dehaene-Lambertzf ; A. Cachiah ; T. Dickscheidd ; O. Coulonb ; C. Poupong ; j ; D. Riviè ; rea ; j ; K. Amuntsd ; i ; Z.Y. Suna ; j
- 关键词：Spatial normalization ; Cortical folding pattern ; Diffeomorphism ; Connectome
- 刊名：Medical Image Analysis
- 出版年：2016
- 出版时间：October 2016
- 年：2016
- 卷：33
- 期：Complete
- 页码：127-133
- 全文大小：2341 K
文摘
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Spatial normalization will have to evolve to improve its architectural compliance.
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Specific research programs are required to select the sulci to be used during normalization.
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Manifold learning is an efficient strategy to model the variability of the cortical folding pattern.
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Connectivity-based parcellations will have a major impact on spatial normalization.