Ontology type: schema:ScholarlyArticle Open Access: True
2013-01
AUTHORSBennett A. Landman, John A. Bogovic, Aaron Carass, Min Chen, Snehashis Roy, Navid Shiee, Zhen Yang, Bhaskar Kishore, Dzung Pham, Pierre-Louis Bazin, Susan M. Resnick, Jerry L. Prince
ABSTRACTMapping 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. More... »
PAGES91-103
http://scigraph.springernature.com/pub.10.1007/s12021-012-9159-9
DOIhttp://dx.doi.org/10.1007/s12021-012-9159-9
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1051192718
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/22932976
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JSON-LD is a popular format for linked data which is fully compatible with JSON.
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This table displays all metadata directly associated to this object as RDF triples.
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17 BLANK NODES