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Construction of multi-scale common brain networks based on DICCCOL.
- Source :
-
Information processing in medical imaging : proceedings of the ... conference [Inf Process Med Imaging] 2013; Vol. 23, pp. 692-704. - Publication Year :
- 2013
-
Abstract
- Modeling the human brain as a network has been widely considered as a powerful approach to investigating the brain's structural and functional systems. However, many previous approaches focused on a single scale of brain network and the multi-scale nature of brain networks has been rarely explored yet. This paper put forward a novel framework to construct multi-scale common networks of brains via multi-scale spectral clustering of fiber connections among DICCCOLs. Specifically, the recently developed and publicly released DICCCOLs provide the nodal structural and functional correspondence across individuals, and thus the employed multi-scale spectral clustering algorithm divided the DICCCOL landmarks and their connections into sub-networks with correspondences on multiple scales. Experimental results showed the promise of the constructed multi-scale networks in applications of structural and functional connectivity mapping. As an application example, these multi-scale networks are used to guide the identification of multi-scale common fiber bundles across individuals and to facilitate the bundle's functional role analysis, which could enable other tract-based and network-based analyses in the future.
- Subjects :
- Algorithms
Humans
Image Enhancement methods
Reproducibility of Results
Sensitivity and Specificity
Brain anatomy & histology
Connectome methods
Diffusion Tensor Imaging methods
Image Interpretation, Computer-Assisted methods
Imaging, Three-Dimensional methods
Nerve Fibers, Myelinated ultrastructure
Nerve Net anatomy & histology
Subjects
Details
- Language :
- English
- ISSN :
- 1011-2499
- Volume :
- 23
- Database :
- MEDLINE
- Journal :
- Information processing in medical imaging : proceedings of the ... conference
- Publication Type :
- Academic Journal
- Accession number :
- 24684010
- Full Text :
- https://doi.org/10.1007/978-3-642-38868-2_58