Evaluating nonlinear coregistration of BOLD EPI and T1 images

Abstract

[1] Hutton et al., 2002. Image Distortion Correction in fMRI: A Quantitative Evaluation. NeuroImage, 16:217–240. [2] Jezzard & Balaban, 1995. Correction for geometric distortion in echo planar images from B0 field variations. Magn Reson Med 34:65-73. [3] Andersson et al., 2003. How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging. NeuroImage, 20:870–88. [4] Kybic et al., 2000. Unwarping of unidirectionally distorted EPI images. IEEE Trans Med Imag , 19:80–93. [5] Studholme et al., 2000. Accurate alignment of functional EPI data to anatomical MRI using a physics-based distortion model. IEEE Trans Med Imag , 19:1115–27. [6] Gholipour et al., 2008. Cross-Validation of Deformable Registration With Field Maps, IEEE J Sel Top Sign. , 2:854–869. [7] Avants et al. , 2008. Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med Imag Anal, 12:26–41. [8] Gorgolewski et al., 2011. Nipype: a flexible , lightweight and extensible neuroimaging data processing framework in Python. Front Neuroinform, 5:13. [9] Kahnt et al., 2012. Connectivity-based parcellation of the human orbitofrontal cortex. J Neurosci 32:6240–50. References For each method, coregistered mean EPI images of all subjects were projected into MNI space, concatenated and averaged over the 4th dimension. The four detail images depict the white box outlined in the whole brain image for each method (x=-8mm). White matter and mask edges of the MNI152 standard brain are overlayed for anatomical reference. While nonlinear coregistration achieves a better fit of the brain outline in frontal regions (white asterisks), fieldmap and topup approach show superior performance in matching gray-white matter boundaries (black asterisk). Different methods for distortion correction show characteristic coregistration outcomes 1