Change search
ReferencesLink to record
Permanent link

Direct link
Analysis of brain activation patterns using a 3-D scale-space primal sketch
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.ORCID iD: 0000-0002-9081-2170
1999 (English)In: Human Brain Mapping, ISSN 1065-9471, E-ISSN 1097-0193, Vol. 7, no 3, 166-94 p.Article in journal (Refereed) Published
Abstract [en]

A fundamental problem in brain imaging concerns how to define functional areas consisting of neurons that are activated together as populations. We propose that this issue can be ideally addressed by a computer vision tool referred to as the scale-space primal sketch. This concept has the attractive properties that it allows for automatic and simultaneous extraction of the spatial extent and the significance of regions with locally high activity. In addition, a hierarchical nested tree structure of activated regions and subregions is obtained. The subject in this article is to show how the scale-space primal sketch can be used for automatic determination of the spatial extent and the significance of rCBF changes. Experiments show the result of applying this approach to functional PET data, including a preliminary comparison with two more traditional clustering techniques. Compared to previous approaches, the method overcomes the limitations of performing the analysis at a single scale or assuming specific models of the data.

Place, publisher, year, edition, pages
1999. Vol. 7, no 3, 166-94 p.
Keyword [en]
brain activation, human brain mapping, functional region, scale-space, primal sketch, scale selection, blob detection, multi-scale representation, computer vision
National Category
Computer Science Computer Vision and Robotics (Autonomous Systems) Neurosciences Bioinformatics (Computational Biology)
URN: urn:nbn:se:kth:diva-40413DOI: 10.1002/(SICI)1097-0193(1999)7:3<166::AID-HBM3>3.0.CO;2-IPubMedID: 10194618OAI: diva2:441151


Available from: 2013-04-16 Created: 2011-09-14 Last updated: 2013-04-16Bibliographically approved

Open Access in DiVA

fulltext(952 kB)318 downloads
File information
File name FULLTEXT01.pdfFile size 952 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMedComplementary information from authors home page

Search in DiVA

By author/editor
Lindeberg, TonyLidberg, Pär
By organisation
Computational Biology, CB
In the same journal
Human Brain Mapping
Computer ScienceComputer Vision and Robotics (Autonomous Systems)NeurosciencesBioinformatics (Computational Biology)

Search outside of DiVA

GoogleGoogle Scholar
Total: 318 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

Altmetric score

Total: 142 hits
ReferencesLink to record
Permanent link

Direct link