Spatial registration and normalization of images

TLDR

The paper discusses spatial and intensity transformations that map one image onto another, with applications to fMRI time‑series realignment, PET and MRI spatial normalization, PET‑MRI coregistration, and PET‑MRI fusion for high‑resolution functional imaging. It proposes a general technique to facilitate nonlinear spatial (stereotactic) normalization and image realignment. The method simultaneously estimates spatial deformations and intensity transformations by minimizing the sum of squares between images using a least‑squares solution and linearizing devices, and is fully automatic, nonlinear, noniterative, and applicable in any dimensionality. © 1995 Wiley‑Liss, Inc.

Abstract

Abstract This paper concerns the spatial and intensity transformations that map one image onto another. We present a general technique that facilitates nonlinear spatial (stereotactic) normalization and image realignment. This technique minimizes the sum of squares between two images following nonlinear spatial deformations and transformations of the voxel (intensity) values. The spatial and intensity transformations are obtained simultaneously, and explicitly, using a least squares solution and a series of linearising devices. The approach is completely noninteractive (automatic), nonlinear, and noniterative. It can be applied in any number of dimensions. Various applications are considered, including the realignment of functional magnetic resonance imaging (MRI) time‐series, the linear (affine) and nonlinear spatial normalization of positron emission tomography (PET) and structural MRI images, the coregistration of PET to structural MRI, and, implicitly, the conjoining of PET and MRI to obtain high resolution functional images. © 1995 Wiley‐Liss, Inc.