MEG–MRI CO-REGISTRATION USING 3D GENERALIZED HOUGH TRANSFORM

Abstract

In this paper, we propose a method to use the three-dimensional (3D) generalized Hough transform (GHT) to co-register magnetoencephalography (MEG) and magnetic resonance imaging (MRI) of a brain automatically, whose results can be used to align MRI images and MEG data accurately and efficiently. Recently, many medical devices have been developed to study the neuronal activity in the human brain. MEG is a high-temporal-resolution measurement tool to study the physiological functions of brain nerves noninvasively; whereas the MRI of the scalp, skull, and cortex of the human brain is a high-spatial-resolution tool. The proposed method combines two tools for investigating the cognitive neuroscience between the human brain structure and weak magnetic fields from two different medical systems. An accurate and automatic registration method is necessitated to improve the brain analysis processes by combining multimodal data. The conventional GHT is a well-known method for detecting two-dimensional (2D) images or locating transformed planar shapes in 2D image processes. To further improve the 2D GHT, we extended it to a 3D GHT, which can co-register MEG and MRI data automatically and accurately. Some experimental results are included to demonstrate and evaluate the error and applicability of MEG–MRI co-registration.