Quantifying gyrification using Laplace Beltrami eigenfunction level-sets

Rosita Shishegar, Jonathan Huntley Manton, David William Walker, Joanne M Britto, Leigh Andrea Johnston

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

4 Citations (Scopus)

Abstract

Cortical surface is folded into gyri and sulci in the brains of higher mammals. Gyrification indices (GI) are widely used to characterise cortical folding complexity, and are important metrics employed in the quantitative assessment of normal brain development and neurodevelopmental disorders. A new GI metric is proposed that endeavours to combine the advantages of surface-based methods with curvature-based methods. The proposed metric employs a measurement of curvature; however, the use of Laplace-Beltrami eigenfunction level-sets introduces the advantage of focusing on folds, a characteristic previously attributed only to surface-based methods. Applying Laplace-Beltrami eigenfunction levelsets also avoids the need to define an outer surface and correspondence function required by surface-based methods. We demonstrate the utility of the proposed GI with an application to fetal ovine MRI data across key developmental time points
Original languageEnglish
Title of host publication2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)
EditorsSebastien Ourselin, Jens Rittscher
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1-4
Number of pages4
DOIs
Publication statusPublished - 2015
EventIEEE International Symposium on Biomedical Imaging (ISBI) 2015 - New York Marriott at Brooklyn Bridge, New York, United States of America
Duration: 16 Apr 201519 Apr 2015
Conference number: 12th

Conference

ConferenceIEEE International Symposium on Biomedical Imaging (ISBI) 2015
Abbreviated titleISBI
CountryUnited States of America
CityNew York
Period16/04/1519/04/15

Keywords

  • gyrification
  • cortical development
  • sulcal shape
  • Laplace Beltrami operator
  • curvature

Cite this

Shishegar, R., Manton, J. H., Walker, D. W., Britto, J. M., & Johnston, L. A. (2015). Quantifying gyrification using Laplace Beltrami eigenfunction level-sets. In S. Ourselin, & J. Rittscher (Eds.), 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI) (pp. 1-4). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ISBI.2015.7164106