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2009 | OriginalPaper | Chapter

Tractography-Based Parcellation of the Cortex Using a Spatially-Informed Dimension Reduction of the Connectivity Matrix

Authors : Pauline Roca, Denis Rivière, Pamela Guevara, Cyril Poupon, Jean-François Mangin

Published in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009

Publisher: Springer Berlin Heidelberg

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Determining cortical functional areas is an important goal for neurosciences and clinical neurosurgery. This paper presents a method for connectivity-based parcellation of the entire human cortical surface, exploiting the idea that each cortex region has a specific connection profile. The connectivity matrix of the cortex is computed using analytical Q-ball-based tractography. The parcellation is achieved independently for each subject and applied to the subset of the cortical surface endowed with enough connections to estimate safely a connectivity profile, namely the top of the cortical gyri. The key point of the method lies in a twofold reduction of the connectivity matrix dimension. First, parcellation amounts to iterating the clustering of Voronoï patches of the cortical surface into parcels endowed with homogeneous profiles. The parcels without intersection with the patch boundaries are selected for the final parcellation. Before clustering a patch, the complete profiles are collapsed into short profiles indicating connectivity with a set of putative cortical areas. These areas are supposed to correspond to the catchment basins of the watershed of the density of connection to the patch computed on the cortical surface. The results obtained for several brains are compared visually using a coordinate system.

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Metadata
Title
Tractography-Based Parcellation of the Cortex Using a Spatially-Informed Dimension Reduction of the Connectivity Matrix
Authors
Pauline Roca
Denis Rivière
Pamela Guevara
Cyril Poupon
Jean-François Mangin
Copyright Year
2009
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-04268-3_115

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