Automatic Co-registration of MEG-MRI Data Using Multiple RGB-D Cameras
Integration of functional and structural modalities is essential to functional brain mapping. This paper presents an automatic co-registration system for aligning the coordinate systems between magnetoencephalography/electroencephalo-graphy (MEG/EEG) and
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Abstract
Integration of functional and structural modalities is essential to functional brain mapping. This paper presents an automatic co-registration system for aligning the coordinate systems between magnetoencephalography/ electroencephalo-graphy (MEG/EEG) and magnetic resonance image (MRI) using multiple off-the-shelf RGBD cameras. The system was constructed by using multiple Kinects for Windows V2, which were calibrated for the integration of the captured data of subjects’ heads from multiple views. The integrated point clouds of the head surface captured by Kinects played an intermediate role between MEG/EEG and MRI. MEG/EEG-to-Kinect co-registration was conducted by using 3D locations of three anatomical landmarks, whereas Kinect-to-MRI co-registration was performed by using Gaussian mixture model to align facial part of points automatically segmented from both Kinect data and MRI. Combination of these two co-registration results yields the MEG/EEGto-MRI transformation. Our evaluation results showed that the proposed system can achieve coordinate system alignment with high accuracy. S.-Y. Lin (&) Y.-S. Chen (&) Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan e-mail: [email protected] Y.-S. Chen e-mail: [email protected] C.-H. Cheng Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan e-mail: [email protected] L.-F. Chen Institute of Brain Science and Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan e-mail: [email protected] L.-F. Chen Integrated Brain Research Unit, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
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Introduction
In brain research fields, noninvasive functional brain mapping using magnetoencephalography (MEG) or electroencephalography (EEG) requires to map the neuronal activity measured on the head surface into the stereotactic space inside the brain, which is called source localization technique. Because source localization requires the locations of EEG electrodes or MEG sensors in the stereotactic coordinate system of magnetic resonance image (MRI), it is essential to align the coordinate system of MEG or EEG to that of MRI in order to integrate the functional activity to the structure of the brain obtained by MRI. Moreover, the accuracy of the coordinate system alignment strongly affect the accuracy of source localization as well as the subsequent interpretation of brain function. Various methods have been proposed to co-register MEG/EEG and MRI coordinate systems. Conventional methods uses locations of anatomical landmarks (left preauricular, or LPA; right preauricular, or RPA; nasion, or NAS) or fiducial points in both modalities to determine a unified coordinate system [1, 2]. Typically, these landmarks are localized using a 3-D digitizer and those in the MRI space are manually specified through visual inspection. Localizing these landmarks is a labor-intensive and operator-dependent task. Poor repeatability is usually another concern, even for an ex
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