English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Group-wise analysis on myelination profiles of cerebral cortex using the second eigenvector of Laplace-Beltrami operator

Kim, S.-G., Stelzer, J., Bazin, P.-L., Viehweger, A., & Knösche, T. R. (2014). Group-wise analysis on myelination profiles of cerebral cortex using the second eigenvector of Laplace-Beltrami operator. In Proceedings of the 11th IEEE International Symposium on Biomedical Imaging (ISBI) (pp. 1007-1010).

Item is

Files

show Files
hide Files
:
Kim_2014_ISBI_finalDraft.pdf (Preprint), 2MB
Name:
Kim_2014_ISBI_finalDraft.pdf
Description:
-
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-

Locators

show

Creators

show
hide
 Creators:
Kim, Seung-Goo1, Author           
Stelzer, Johannes2, Author           
Bazin, Pierre-Louis2, 3, Author           
Viehweger, Adrian4, Author
Knösche, Thomas R.1, Author           
Affiliations:
1Methods and Development Group MEG and EEG - Cortical Networks and Cognitive Functions, MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_2205650              
2Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634550              
3Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_634549              
4External Organizations, ou_persistent22              

Content

show
hide
Free keywords: Myelination profile; Heschl's gyrus; Group-level analysis; Laplace-Beltrami eigenvector
 Abstract: Myeloarchitecture of cerebral cortex has crucial implication on the function of cortical columnar modules. Based on the recent development of high-field magnetic resonance imaging (MRI), it was demonstrated that it is possible to individually reconstruct such intracortical microstructures. However, there is a scarcity of publicly available frameworks to perform group-wise statistical inferences on high resolution data. In this paper, we present a novel framework that parameterizes curved brain structures in order to construct correspondences across subjects without deforming individual geometry. We use the second Laplace-Beltrami eigenfunction to build such a parameterization, which is known to monotonically increase along the longest geodesic distance on an arbitrary manifold. To demonstrate our framework, a study on the lateralization of Heschl’s gyrus is presented with multiple comparison correction.

Details

show
hide
Language(s): eng - English
 Dates: 2014-04-29
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1109/ISBI.2014.6868043
 Degree: -

Event

show
hide
Title: The 11th IEEE International Symposium on Biomedical Imaging (ISBI)
Place of Event: Beijing, China
Start-/End Date: 2014-04-29 - 2014-05-02

Legal Case

show

Project information

show

Source 1

show
hide
Title: Proceedings of the 11th IEEE International Symposium on Biomedical Imaging (ISBI)
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1007 - 1010 Identifier: -