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Rotational invariance in adaptive fMRI data analysis
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, The Institute of Technology.
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9091-4724
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9267-2191
2006 (English)In: Image Processing, 2006, IEEE , 2006, 2841-2844 p.Conference paper, Published paper (Refereed)
Abstract [en]

It has previously been shown that canonical correlation analysis (CCA) works well for detecting neural activity in fMRI data. This is due to the ability of CCA to perform simultaneous temporal modeling and adaptive spatial filtering of the data. In this paper, we demonstrate that our previously proposed method for CCA-based fMRI data analysis does not provide rotationally invariant detection of activated regions. We propose a modification of the previous method and show that it resolves the rotational invariance issue, thereby further improving the analysis method

Place, publisher, year, edition, pages
IEEE , 2006. 2841-2844 p.
Series
International Conference on Image Processing. Proceedings, ISSN 1522-4880
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-34137DOI: 10.1109/ICIP.2006.313000ISI: 000245768501329Local ID: 20911OAI: oai:DiVA.org:liu-34137DiVA: diva2:254985
Conference
IEEE International Conference on Image Processing (ICIP 2006), 8-10 October 2006, Atlanta, GA, USA
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2015-10-09

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Rydell, JoakimKnutsson, HansBorga, Magnus

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  • de-DE
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  • sv-SE
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Output format
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