liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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
Efficient representations in matlab made easy - a tensor array toolbox
Linköping University, Department of Medicine and Care. Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Health Sciences.
2001 (English)In: Proceedings of Nordic Matlab Conference, 2001, 2001, 213-216 p.Conference paper, Published paper (Refereed)
Abstract [en]

Tensors can be used to create efficient and intuitive representations for a wide variety of applications, including signal and image processing, mechanics and fluid dynamics. In order to achieve this in Matlab, a toolbox was developed designed to enhance Matlab's ability to store and manipulate arrays, such that each element in the array can be vectors or general tensors. This paper describes the implementation of the tool box and gives several examples on the usage of tensor representations for signal and image processing. Furthermore, the representation and processing of uncertain data using tensor representations is described as well.

Place, publisher, year, edition, pages
2001. 213-216 p.
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-27346Local ID: 11998OAI: oai:DiVA.org:liu-27346DiVA: diva2:247897
Conference
Nordic Matlab Conference. 17-18 Oct, Oslo, Norway, 2001
Available from: 2009-10-08 Created: 2009-10-08 Last updated: 2013-11-07
In thesis
1. Automated feature detection in multidimensional images: a unified tensor approach
Open this publication in new window or tab >>Automated feature detection in multidimensional images: a unified tensor approach
2001 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Manual identification of structures and features in multidimensional images is at best time consuming and operator dependent. Feature identification need to be accurate, repeatable and quantitative. This thesis presents a unified approach for automatic feature detection in multidimensional scalar and vector fields. The basis for the feature detection is a tensor representation of multidimensional local neighborhoods, constructed from a filter response controlled linear combination of basis tensors. Using eigenvalue and eigenvector decomposition, local topology and local orientation can be estimated. With different filter sets the tensor representation can be used to find specific features in multidimensional images, such as planar structures in scalar fields or flow structures as vortices or parallel flow in vector fields.

The motivation for the unified approach for feature detection in both scalar and vector fields is to build a foundation to tackle the challenge of understanding the complex interaction between the cardiac walls and the blood flow in the human heart.

Place, publisher, year, edition, pages
Linköping: Linköpings universitet, 2001. 42 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 909
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-33625 (URN)LiU-TEK-LIC-2001:46 (Local ID)91-7373-131-5 (ISBN)LiU-TEK-LIC-2001:46 (Archive number)LiU-TEK-LIC-2001:46 (OAI)
Presentation
2001-11-30, Terassen, Universitetssjukhuset, Linköping, 10:15 (Swedish)
Opponent
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2013-11-07Bibliographically approved

Open Access in DiVA

No full text

Other links

http://physics.bgu.ac.il/~quantum/isaac/MatlabWorks/paper3.pdf

Authority records BETA

Brandt Heiberg, Einar

Search in DiVA

By author/editor
Brandt Heiberg, Einar
By organisation
Department of Medicine and CareDepartment of Biomedical EngineeringFaculty of Health Sciences
Medical and Health Sciences

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 46 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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