Exploration of the Brain's White Matter Pathways with Dynamic Queries
VIS '04 Proceedings of the conference on Visualization '04
Functional Identification of Retinal Ganglion Cells Based on Neural Population Responses
IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks
Searching for semantics in the retinal code
Neurocomputing
Tractography Segmentation Using a Hierarchical Dirichlet Processes Mixture Model
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
International Journal of Computer Vision
Hierarchical fiber clustering based on multi-scale neuroanatomical features
MIAR'10 Proceedings of the 5th international conference on Medical imaging and augmented reality
Fiber modeling and clustering based on neuroanatomical features
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part II
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This work presents a framework driven by parcellation of brain gray matter in standard normalized space to classify the neuronal fibers obtained from diffusion tensor imaging (DTI) in entire human brain. Classification of fiber bundles into groups is an important step for the interpretation of DTI data in terms of functional correlates of white matter structures. Connections between anatomically delineated brain regions that are considered to form functional units, such as a short-term memory network, are identified by first clustering fibers based on their terminations in anatomically defined zones of gray matter according to Talairach Atlas, and then refining these groups based on geometric similarity criteria. Fiber groups identified this way can then be interpreted in terms of their functional properties using knowledge of functional neuroanatomy of individual brain regions specified in standard anatomical space, as provided by functional neuroimaging and brain lesion studies.