Simultaneous correction for interscan patient motion and geometric distortions in echoplanar imaging

Abstract

A method is presented for simultaneous correction of linear geometric distortions and interscan patient motion in echoplanar imaging (EPI). The technique does not require the acquisition of specialized scans other than high-resolution magnetic resonance images. The method is based on a generalized surface-based coregistration algorithm, which accounts for a complete 3-dimensional affine transformation, i.e., rotations, translations, scaling, and shearing, between two volumetric image data sets. Any minimally distorted high-resolution scan may serve as a reference data set, to which the EPI data set is matched. The algorithmic accuracy was assessed using simulated data sets with known affine distortions. The deviation of the parameters determined by the coregistration program from the true values typically was 1% or less. Precise alignment of functional and anatomic information will be important for many future clinical applications. Magn Reson Med 42:201-

Perfusion MRI of the human brain with dynamic susceptibility contrast: Gradient-echo versus spin-echo techniques

“…During this coregistration, geometric distortions of the EPI data sets as well as interscan subject motion were corrected using a full affine transformation that also accounts for possible scaling or shearing in the phase direction (23).…”

Brain Functional Localization: A Survey of Image Registration Techniques

“…Discussion of these techniques is beyond the scope of this survey paper, while it is noted that these techniques cannot completely correct the effect of nonlinear distortion artifacts and nonrigid registration can be effective in reducing the local mis-registrations caused between functional and anatomical images. A few studies have relied on affine transformation for distortion correction via registration of EPI to an anatomical image [153], [154], while most of the others have utilized high-dimensional nonrigid transformations [155]- [162]. The transformation models that have been used in these studies include unidirectional B-spline basis functions [156], Optical flow (OF) model [107], [155], [159], [160], and free form deformation (FFD) with regular grid of control points [157], [158], [161], [162].…”

“…Hence, qualitative assessment of registration fidelity through visual inspection is also useful. Qualitative assessment of registration accuracy has been done mostly through simple visualization techniques incorporating segmented edges and contours or checkerboard alignment of images through visual inspection [87], [88], [90], [96], [102], [107], [112], [131], [132], [134], [141], [149], [153], [155], [156], [160], [165], [166], [168]. It is often useful for registration results for real data to be cross-validated by comparing the accuracy of registration judged by expert observers with other evaluation criteria.…”

“…The practical papers that have addressed the problem of fMRI EPI-to-anatomical MRI registration have typically relied on additional validation strategies. The technique in [153] has shown to be able to correct the effect of intentionally mis-adjusted shimming in EPI. Comparison of the transformation deformation fields to real field map acquisitions has been used in [157] and [162].…”

Correction of spatial distortion in EPI due to inhomogeneous static magnetic fields using the reversed gradient method

“…A number of other methods have been described that rely on information gathered from MR images of phantoms of known physical dimensions, and the use of mathematical transformations (17,18). While adequate distortion correction can be achieved with these methods under some circumstances, since they incorporate smoothly varying functions, one would not expect the correction to be as accurate as that obtained by methods that correct each point independently.…”