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  System for integrated neuroimaging analysis and processing of structure

Landman, B. A., Bogovic, J. A., Carass, A., Chen, M., Roy, S., Shiee, N., et al. (2013). System for integrated neuroimaging analysis and processing of structure. Neuroinformatics, 11(1), 91-103. doi:10.1007/s12021-012-9159-9.

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 Creators:
Landman, Bennett A.1, 2, 3, Author
Bogovic, John A.4, Author
Carass, Aaron4, Author
Chen, Min4, Author
Roy, Snehashis4, Author
Shiee, Navid4, Author
Yang, Zhen4, Author
Kishore, Bhaskar5, Author
Pham, Dzung4, 5, 6, Author
Bazin, Pierre-Louis7, Author              
Resnick, Susan M.8, Author
Prince, Jerry L.2, 4, 5, Author
Affiliations:
1Department of Electrical Engineering, Vanderbilt University, 2301 Vanderbilt Pl., Station B, PO Box 351679, Nashville, TN 37235-1679, USA, ou_persistent22              
2Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA, ou_persistent22              
3The Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA, ou_persistent22              
4Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA, ou_persistent22              
5The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA, ou_persistent22              
6Center for Neuroscience and Regenerative Medicine, Washington, DC, USA, ou_persistent22              
7Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634550              
8Laboratory of Personality and Cognition, National Institute on Aging, Baltimore, MD, USA, ou_persistent22              

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Free keywords: Brain; MRI; Cortical surface; White matter parcellation; Fiber tracking; Sub-cortical segmentation
 Abstract: Mapping brain structure in relation to neurological development, function, plasticity, and disease is widely considered to be one of the most essential challenges for opening new lines of neuro-scientific inquiry. Recent developments with MRI analysis of structural connectivity, anatomical brain segmentation, cortical surface parcellation, and functional imaging have yielded fantastic advances in our ability to probe the neurological structure-function relationship in vivo. To date, the image analysis efforts in each of these areas have typically focused on a single modality. Here, we extend the cortical reconstruction using implicit surface evolution (CRUISE) methodology to perform efficient, consistent, and topologically correct analyses in a natively multi-parametric manner. This effort combines and extends state-of-the-art techniques to simultaneously consider and analyze structural and diffusion information alongside quantitative and functional imaging data. Robust and consistent estimates of the cortical surface extraction, cortical labeling, diffusion-inferred contrasts, diffusion tractography, and subcortical parcellation are demonstrated in a scan-rescan paradigm. Accompanying this demonstration, we present a fully automated software system complete with validation data.

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Language(s): eng - English
 Dates: 2012-08-302013-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1007/s12021-012-9159-9
PMID: 22932976
PMC: PMC3511612
 Degree: -

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Title: Neuroinformatics
Source Genre: Journal
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Publ. Info: Humana Press
Pages: - Volume / Issue: 11 (1) Sequence Number: - Start / End Page: 91 - 103 Identifier: ISSN: 1539-2791
CoNE: https://pure.mpg.de/cone/journals/resource/1539-2791