Literature DB >> 23286048

Resting-state FMRI single subject cortical parcellation based on region growing.

Thomas Blumensath1, Timothy E J Behrens, Stephen M Smith.   

Abstract

We propose a new method to parcellate the cerebral cortex based on spatial dependancy in the fluctuations observed with functional Magnetic Resonance Imaging (fMRI) during rest. Our surface-based approach uses a region growing method. In contrast to previous methods, locally stable seed points are identified on the cortical surface and these are grown into a (relatively large 1000 to 5000) number of spatially contiguous regions on both hemispheres. Spatially constrained hierarchical clustering is then used to further combine these regions in a hierarchical tree. Using short-TR resting state fMRI data, this approach allows a subject specific parcellation of the cortex into anatomically plausible subregions, identified with high scan-to-scan reproducibility and with borders that delineate clear changes in functional connectivity.

Mesh:

Year:  2012        PMID: 23286048     DOI: 10.1007/978-3-642-33418-4_24

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  7 in total

1.  GraSP: geodesic Graph-based Segmentation with Shape Priors for the functional parcellation of the cortex.

Authors:  N Honnorat; H Eavani; T D Satterthwaite; R E Gur; R C Gur; C Davatzikos
Journal:  Neuroimage       Date:  2014-11-11       Impact factor: 6.556

2.  A hybrid high-resolution anatomical MRI atlas with sub-parcellation of cortical gyri using resting fMRI.

Authors:  Anand A Joshi; Soyoung Choi; Yijun Liu; Minqi Chong; Gaurav Sonkar; Jorge Gonzalez-Martinez; Dileep Nair; Jessica L Wisnowski; Justin P Haldar; David W Shattuck; Hanna Damasio; Richard M Leahy
Journal:  J Neurosci Methods       Date:  2022-03-17       Impact factor: 2.987

3.  Individual-Specific Areal-Level Parcellations Improve Functional Connectivity Prediction of Behavior.

Authors:  Ru Kong; Qing Yang; Evan Gordon; Aihuiping Xue; Xiaoxuan Yan; Csaba Orban; Xi-Nian Zuo; Nathan Spreng; Tian Ge; Avram Holmes; Simon Eickhoff; B T Thomas Yeo
Journal:  Cereb Cortex       Date:  2021-08-26       Impact factor: 5.357

4.  δ-MAPS: from spatio-temporal data to a weighted and lagged network between functional domains.

Authors:  Ilias Fountalis; Constantine Dovrolis; Annalisa Bracco; Bistra Dilkina; Shella Keilholz
Journal:  Appl Netw Sci       Date:  2018-07-31

5.  Spatially constrained hierarchical parcellation of the brain with resting-state fMRI.

Authors:  Thomas Blumensath; Saad Jbabdi; Matthew F Glasser; David C Van Essen; Kamil Ugurbil; Timothy E J Behrens; Stephen M Smith
Journal:  Neuroimage       Date:  2013-03-21       Impact factor: 6.556

6.  Which fMRI clustering gives good brain parcellations?

Authors:  Bertrand Thirion; Gaël Varoquaux; Elvis Dohmatob; Jean-Baptiste Poline
Journal:  Front Neurosci       Date:  2014-07-01       Impact factor: 4.677

7.  Ant Colony Clustering for ROI Identification in Functional Magnetic Resonance Imaging.

Authors:  Alejandro Veloz; Alejandro Weinstein; Stefan Pszczolkowski; Luis Hernández-García; Rodrigo Olivares; Roberto Muñoz; Carla Taramasco
Journal:  Comput Intell Neurosci       Date:  2019-12-26
  7 in total

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