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Proceedings Paper

A whole brain atlas with sub-parcellation of cortical gyri using resting fMRI
Author(s): Anand A. Joshi; Soyoung Choi; Gaurav Sonkar; Minqi Chong; Jorge Gonzalez-Martinez; Dileep Nair; David W. Shattuck; Hanna Damasio; Richard M. Leahy
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Paper Abstract

The new hybrid-BCI-DNI atlas is a high-resolution MPRAGE, single-subject atlas, constructed using both anatomical and functional information to guide the parcellation of the cerebral cortex. Anatomical labeling was performed manually on coronal single-slice images guided by sulcal and gyral landmarks to generate the original (non-hybrid) BCI-DNI atlas. Functional sub-parcellations of the gyral ROIs were then generated from 40 minimally preprocessed resting fMRI datasets from the HCP database. Gyral ROIs were transferred from the BCI-DNI atlas to the 40 subjects using the HCP grayordinate space as a reference. For each subject, each gyral ROI was subdivided using the fMRI data by applying spectral clustering to a similarity matrix computed from the fMRI time-series correlations between each vertex pair. The sub-parcellations were then transferred back to the original cortical mesh to create the subparcellated hBCI-DNI atlas with a total of 67 cortical regions per hemisphere. To assess the stability of the gyral subdivisons, a separate set of 60 HCP datasets were processed as follows: 1) coregistration of the structural scans to the hBCI-DNI atlas; 2) coregistration of the anatomical BCI-DNI atlas without functional subdivisions, followed by sub-parcellation of each subject’s resting fMRI data as described above. We then computed consistency between the anatomically-driven delineation of each gyral subdivision and that obtained per subject using individual fMRI data. The gyral sub-parcellations generated by atlas-based registration show variable but generally good overlap of the confidence intervals with the resting fMRI-based subdivisions. These consistency measures will provide a quantitative measure of reliability of each subdivision to users of the atlas.

Paper Details

Date Published: 2 March 2017
PDF: 9 pages
Proc. SPIE 10133, Medical Imaging 2017: Image Processing, 101330O (2 March 2017); doi: 10.1117/12.2254681
Show Author Affiliations
Anand A. Joshi, The Univ. of Southern California (United States)
Soyoung Choi, The Univ. of Southern California (United States)
Gaurav Sonkar, National Institute of Technology, Warangal (India)
Minqi Chong, The Univ. of Southern California (United States)
Jorge Gonzalez-Martinez, Cleveland Clinic Foundation (United States)
Dileep Nair, Cleveland Clinic Foundation (United States)
David W. Shattuck, Univ. of California, Los Angeles (United States)
Hanna Damasio, The Univ. of Southern California (United States)
Richard M. Leahy, The Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 10133:
Medical Imaging 2017: Image Processing
Martin A. Styner; Elsa D. Angelini, Editor(s)

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