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On Structural Based Certainty for Robust fMRI 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.
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
(English)Manuscript (preprint) (Other academic)
Abstract [en]

We present a method for obtaining and using a structural based certainty for robust functional magnetic resonance imaging (fMRI) analysis. In the area of fMRI it is common to see brain activity maps with activity at the edge of the brain. It is however a known fact that activity close to the edge of the brain can be due to head movement, since the voxels close to the edge will have a higher variance if they switch between being outside and inside the brain. To some extent this can be remedied by aligning each volume to a reference volume, by the means of volume registration. However, the problem with fMRI volumes is that the slices in the volume normally are taken at different timepoints, and motion between the slices can occur. We calculate a structural based certainty for each voxel, from a high resolution T1-weighted volume, and incorporate this certainty into the statistical analysis of the fMRI data. We show that our certainty approach removes a lot of false activity, both on simulated data and on real data.

National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-54039OAI: oai:DiVA.org:liu-54039DiVA: diva2:297938
Available from: 2010-02-19 Created: 2010-02-19 Last updated: 2013-08-28
In thesis
1. Signal Processing for Robust and Real-Time fMRI With Application to Brain Computer Interfaces
Open this publication in new window or tab >>Signal Processing for Robust and Real-Time fMRI With Application to Brain Computer Interfaces
2010 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

It is hard to find another research field than functional magnetic resonance imaging (fMRI) that combines so many different areas of research. Without the beautiful physics of MRI we would not have any images to look at in the first place. To get images with good quality it is necessary to fully understand the concepts of the frequency domain. The analysis of fMRI data requires understanding of signal processing and statistics and also knowledge about the anatomy and function of the human brain. The resulting brain activity maps are used by physicians and neurologists in order to plan surgery and to increase their understanding of how the brain works.

This thesis presents methods for signal processing of fMRI data in real-time situations. Real-time fMRI puts higher demands on the signal processing, than conventional fMRI, since all the calculations have to be made in realtime and in more complex situations. The result from the real-time fMRI analysis can for example be used to look at the subjects brain activity in real-time, for interactive planning of surgery or understanding of brain functions. Another possibility is to use the result in order to change the stimulus that is given to the subject, such that the brain and the computer can work together to solve a given task. These kind of setups are often called brain computer interfaces (BCI).

Two BCI are presented in this thesis. In the first BCI the subject was able to balance a virtual inverted pendulum by thinking of activating the left or right hand or resting. In the second BCI the subject in the MR scanner was able to communicate with a person outside the MR scanner, through a communication interface.

Since head motion is common during fMRI experiments it is necessary to apply image registration to align the collected volumes. To do image registration in real-time can be a challenging task, therefore how to implement a volume registration algorithm on a graphics card is presented. The power of modern graphic cards can also be used to save time in the daily clinical work, an example of this is also given in the thesis.

Finally a method for calculating and incorporating a structural based certainty in the analysis of the fMRI data is proposed. The results show that the structural certainty helps to remove false activity that can occur due to head motion, especially at the edge of the brain.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2010. 130 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1432
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-54040 (URN)LIU-TEK-LIC-2010:3 (Local ID)978-91-7393-431-2 (ISBN)LIU-TEK-LIC-2010:3 (Archive number)LIU-TEK-LIC-2010:3 (OAI)
Presentation
2010-03-09, Wranne-salen, CMIV, plan 11, Campus US, Linköpings universitet, Linköping, 14:00 (English)
Opponent
Supervisors
Available from: 2010-02-19 Created: 2010-02-19 Last updated: 2013-08-28Bibliographically approved

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Eklund, AndersAndersson, MatsKnutsson, Hans

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