• Theodore Arsenault, Fang Fang Yin, Junzo Chino, Oana Craciunescu, and Jim Zheng Chang.
• Department of Radiation Oncology, Duke University, Durham, NC, United States of America.
• Phys Med Biol. 2021 Jan 29; 66 (3): 035021.

AbstractTo investigate the feasibility of the log-demons deformable image registration (DIR) method to correct eddy current and field inhomogeneity distortions while preserving diffusion tensor information. Diffusion-weighted images (DWIs) are susceptible to distortions caused by eddy current and echo-planar imaging (EPI) gradients. We propose a post-acquisition correction algorithm using the log-demons DIR technique for eddy current and field inhomogeneity distortions of DWI. The new correction technique was applied to DWI acquired using a diffusion phantom and the multiple acquisitions for standardization of structural imaging validation and evaluation (MASSIVE) brain database. This method is compared to previous methods using cross-correlation, mutual information (MI). In the phantom study, the log-demons algorithm reduced eddy current and field inhomogeneity distortions while preserving diffusion tensor information when compared to affine and demon's registration techniques. Analysis of the tensor metrics using percent difference and the root mean square of the apparent diffusion coefficient and fractional anisotropy found that the log-demons algorithm outperforms the other algorithms in terms of preserving diffusion information. In the MASSIVE study, the average MI of all slices increased for both eddy current and field inhomogeneity distortion correction. The average absolute differences of all slices between corrected images with opposing gradients were also on average decreased. This work indicates that the log-demons DIR algorithm is feasible to reduce eddy current and field inhomogeneity distortions while preserving quantitative diffusion information.

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