Authors:
Tali Lerner
;
Ehud Rivlin
and
Moshe Gur
Affiliation:
Technion-Israel Institute of Technology, Israel
Keyword(s):
fMRI, pose estimation, motion correction, tracking.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Human-Computer Interaction
;
Methodologies and Methods
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Physiological Computing Systems
;
Stereo Vision and Structure from Motion
Abstract:
This paper presents a new vision-based system for motion correction in functional-MRI experiments. fMRI is a popular technique for studying brain functionality by utilizing MRI technology. In an fMRI experiment a subject is required to perform a task while his brain is scanned by an MRI scanner. In order to achieve a high quality analysis the fMRI slices should be aligned. Hence, the subject is requested to avoid head movements during the entire experiment. However, due to the long duration of such experiments head motion is practically unavoidable. Most of the previous work in this field addresses this problem by extracting the head motion parameters from the acquired MRI data. Therefore, these works are limited to relatively small movements and may confuse head motion with brain activities. In the present work the head movements are detected by a system comprised of two cameras that monitor a specially designed device worn on the subject’s head. The system does not depend on the ac
quired MRI data and therefore can overcome large head movements. Additionally, the system can be extended to cope with inter-block motion and can be integrated into the MRI scanner for real-time updates of the scan-planes. The performance of the proposed system was tested in a laboratory environment and in fMRI experiments. It was found that high accuracy is obtained even when facing large head movements.
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