Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/52836

TitleA framework for the automation of multimodalbrain connectivity analyses
Author(s)Marques, Paulo César Gonçalves
Soares, José Miguel Montenegro
Magalhães, Ricardo José Silva
Sousa, Nuno
Alves, Victor
Issue date2016
PublisherSpringer
JournalStudies in Computational Intelligence
Abstract(s)In neuroscience research, there has been an increasing interest in multimodal analysis, combining the strengths of unimodal analysis while reducing some of its drawbacks. However, this increases complexity in data processing and analysis, requiring a big amount of technical knowledge in image manipulation and a lot of iterative processes requiring user intervention. In this work we present a framework that incorporates some of this technical knowledge and enables the automation of most of the processing in the context of combined resting-state functional Magnetic Resonance Imaging (rs-fMRI) and Diffusion Tensor Imaging (DTI) data processing and analysis. The proposed framework presents an object-oriented architecture and its structure reflects the nature of three levels of data processing (i.e. acquisition level, subject level and study level). This framework opens the door to more intelligent and scalable systems for neuroimaging data processing and analysis that ultimately will lead to the dissemination of such advanced techniques.
TypeConference paper
URIhttp://hdl.handle.net/1822/52836
ISBN978-3-319-25015-1
e-ISBN978-3-319-25017-5
DOI10.1007/978-3-319-25017-5_34
ISSN1860-949X
Publisher versionhttps://link.springer.com/book/10.1007/978-3-319-25017-5
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Livros e capítulos de livros/Books and book chapters

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