Accurate alignment of functional EPI data to anatomical MRI using a physics-based distortion model

Abstract

Mapping of functional magnetic resonance imaging (fMRI) to conventional anatomical MRI is a valuable step in the interpretation of fMRI activations. One of the main limits on the accuracy of this alignment arises from differences in the geometric distortion induced by magnetic field inhomogeneity. This paper describes an approach to the registration of echo planar image (EPI) data to conventional anatomical images which takes into account this difference in geometric distortion. We make use of an additional spin echo EPI image and use the known signal conservation in spin echo distortion to derive a specialized multimodality nonrigid registration algorithm. We also examine a plausible modification using log-intensity evaluation of the criterion to provide increased sensitivity in areas of low EPI signal. A phantom-based imaging experiment is used to evaluate the behavior of the different criteria, comparing nonrigid displacement estimates to those provided by a imagnetic field mapping acquisition. The algorithm is then applied to a range of nine brain imaging studies illustrating global and local improvement in the anatomical alignment and localization of fMRI activations.

Geometric distortion correction for echo planar images using nonrigid registration with spatially varying scale

“…Thus, the displacement at location (x, y, z) can be written as (1) where Δy(x, y, z) is the geometric distortion at the original position (x, y, z) and is calculated by: (2) Here, γ̶ is the gyromagnetic ratio, ΔB is the perturbation of the B 0 field, and FOV y and BW y are the Field of View and bandwidth in the phase encoding direction, respectively.…”

“…However, EPI images are known to be prone to geometric and intensity distortions. Nonrigid registration-based methods have been used to correct for these distortions [1]- [5]. Such methods, by registering an EPI image to a reference image with no distortion or negligible distortion, generate a deformation field that is then applied to the EPI image to produce a corrected one.…”

Functional magnetic resonance imaging: A review of methodological aspects and clinical applications

“…3). The problem becomes increasingly severe at higher fields; therefore, methods for distortion corrections have found increasing interest (27)(28)(29)(30)(31)(32)(33)35). All of these approaches are based on measurements of local field variations by additional field map measurements integrated into the examination.…”

Incorporating DTI Data as a Constraint in Deformation Tensor Morphometry Between T1 MR Images

“…The DTI data of each study was reconstructed into a rank 2 tensor and the b=0 image was rigidly and then non-rigidly aligned to the T1 MPRAGE data using a method derived from [13]. The non-rigid deformation estimate of the data was then applied to bring the diffusion tensors into the coordinate system and sampling resolution of the MPRAGE data (using cubic interpolation), taking into account the local change in geometry using the method of preservation of principal directions [1].…”