关键词: 功能磁共振成像, 运动校正, 刚体变换

Abstract: In brain functional Magnetic Resonance Imaging (fMRI) experiment, motion correction is an important step in data preprocessing. Results of motion correction affect the follow up analysis such as detecting the functional activation area and functional connectivity. There are some simplified hypotheses for head motion in the common analysis software packages. Due to large volume of data, the correction error is also large. In order to reduce the correction error, a novel motion correction method was proposed based on local rigid transform. This method first used adjacent weighted slices to construct local volumetric data for each slice in a multi-slice echo planar imaging volume data, and then estimated the space position of each slice by the registration of local volumetric data using the modified Gauss-Newton optimization algorithm. Finally the image stack was re-sliced using Delaunay triangulation method. Results of implementation based on this method during phantom data and human vision experiments reveal that it is effective to reduce the correction error, which leads to accurate realignment.

Key words: functional Magnetic Resonance Imaging (fMRI), motion correction, rigid transformation