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In neuroimaging, spatial normalization is an image processing step, more specifically an image registration method. Human brains differ in size and shape, and one goal of spatial normalization is to deform human brain scans so one location in one subject's brain scan corresponds to the same location in another subject's brain scan. It is often performed in research-based functional neuroimaging where one wants to find common brain activation across multiple human subjects. The brain scan can be obtained from magnetic resonance imaging (MRI) or positron emission tomography (PET) scanners. There are two steps in the spatial normalization process: * Specification/estimation of warp-field * Application of warp-field with resampling The estimation of the warp-field can be performed in one modality, e.g., MRI, and be applied in another modality, e.g., PET, if MRI and PET scans exist for the same subject and they are coregistered. Spatial normalization typically employs a 3-dimensional nonrigid transformation model (a "warp-field") for warping a brain scan to a template. The warp-field might be parametrized by basis functions such as cosine and polynomia. There is a number of programs that implement both estimation and application of a warp-field. It is a part of the SPM and AIR programs. ==See also== * Voxel-based morphometry 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Spatial normalization」の詳細全文を読む スポンサード リンク
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