Digitala Vetenskapliga Arkivet

Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Graph Spectral Characterization of Brain Cortical Morphology
independent researcher, Vienna, Austria.
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Science & Engineering.
Department of Biomedical Engineering, Lund University, Lund, Sweden.
2019 (English)In: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019Conference paper, Published paper (Refereed)
Abstract [en]

The human brain cortical layer has a convoluted morphology that is unique to each individual. Characterization of the cortical morphology is necessary in longitudinal studies of structural brain change, as well as in discriminating individuals in health and disease. A method for encoding the cortical morphology in the form of a graph is presented. The design of graphs that encode the global cerebral hemisphere cortices as well as localized cortical regions is proposed. Spectral metrics derived from these graphs are then studied and proposed as descriptors of cortical morphology. As proof-of-concept of their applicability in characterizing cortical morphology, the metrics are studied in the context of hemispheric asymmetry as well as gender dependent discrimination of cortical morphology.

Place, publisher, year, edition, pages
2019.
Series
Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), ISSN 1557-170X, E-ISSN 1558-4615
Keywords [en]
Morphology, Eigenvalues and eigenfunctions, Measurement, Shape, Laplace equations, Symmetric matrices, Encoding
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:liu:diva-160933DOI: 10.1109/EMBC.2019.8856468ISI: 000557295300106ISBN: 978-1-5386-1311-5 (electronic)ISBN: 978-1-5386-1312-2 (print)OAI: oai:DiVA.org:liu-160933DiVA, id: diva2:1361172
Conference
41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 23-27 July 2019
Note

Funding agencies: Swedish Research CouncilSwedish Research Council [2018-06689]

Available from: 2019-10-15 Created: 2019-10-15 Last updated: 2020-09-12Bibliographically approved

Open Access in DiVA

fulltext(1186 kB)296 downloads
File information
File name FULLTEXT01.pdfFile size 1186 kBChecksum SHA-512
5a771fa054c2902c256c6643a976ced5c41bbff0833cdd189d0c56711e5023b4db0378b758ca973dc95da6f7a192f422593b961227bde0f3ffebd793e2c27948
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Eklund, Anders
By organisation
Division of Biomedical EngineeringThe Division of Statistics and Machine LearningFaculty of Science & Engineering
Medical Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 296 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 177 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf