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ACID - Artefact correction in diffusion MRI / ACID_wiki_hysco

Short overview

HySCO is an academic software for the correction of susceptibility artifacts in diffusion weighted images based on a reversed gradient based acquisition scheme. It is developed by Lars Ruthotto and Jan Modersitzki as an add-on to the registration toolbox FAIR.

HySCO requires the acquisition of a pair of images with reversed phase-encoding gradients that are oppositely affected by distortions. From the so-called "blip-up" and "blip-down" image data, HySCO estimates the field-inhomogeneity by solving a tailored image registration problem that incorporates a physical model of inhomogeneity artifacts in spin-echo MRI.

HySCO's name-giving component is a special non-linear regularization functional, which is inspired by hyperelasticity. It ensures smoothness of the field inhomogeneity and invertibility of the geometrical transformations regardless of the actual choice of regularization parameters.

The HySCO GUI Fig. 1: HySCO within the ACID-SC toolbox.

Preprocessing

Prior to applying HySCO, the dMRI dataset has to be corrected for intra-subject (between-volume) displacements using ECMOCO: Importantly, apply ECMOCO on the blip-up and blip-down images separately?

Usage

  • Reference blip-up image: Select one reference image volume acquired with blip-up phase encoding direction (b=0 image is recommended, because it has higher SNR). Note that the ''true'' blip-up and down directions can be unknown! Just define here one DTI dataset as ''blip-up'' and the other as 'blip-down'. The field inhomogeneity is estimated by minimizing the sum-of-squared difference between this image and the blip-down image chosen below and regularization.

  • Reference blip-down image: Select one reference image volume acquired with blip-down phase encoding direction (see above for details).

  • Other blip-up images: (optional) Choose ''other image volumes'' acquired with blip-up phase encoding direction. The data is corrected by applying the transformation estimated by the reference blip-up/down data. If an equal number of blip-up and blip-down data is provided as ''other image volumes'', you may also want to disable ''Apply to other images'' (see 7).

  • Other blip-down images: (optional) Choose ''other image volumes'' acquired with blip-down phase encoding direction.

  • Dimension of phase-encoding: Specify the phase-encoding direction of your data (i.e. the direction in which the susceptibility distortions will be greatest). Default is y-direction.

  • Maximal data resolution: Choose the finest discretization level for field inhomogeneity estimation. If set to ''full'' a multi-level strategy with three discretization levels is used, where the resolution on the finest level equals the data resolution. To save computation time, choose ''half''. The multi-level scheme will be stopped after the second level (i.e. half of data resolution) and the inhomogeneity estimate will be interpolated to the data resolution.

  • Apply to other images: If set to ''no'' and if the same number of diffusion-weighted images is provided for blip-up and blip-down, the field inhomogeneities are estimated for each set of blip-up/down images separately (This might be useful to correct in addition to susceptibility-induced distortion for the distortions due to nonlinear eddy current fields). To this end, the field-inhomogeneity estimated from the non-diffusion weighted images is used as a starting guess for minimization of the distance between the respective diffusion-weighted image pairs. Optimization is only carried out on the finest discretization level to save computation time.

Output

  • Field homogeneity map: Estimated from the pairs of blip-up and blip-down images and saved .

  • HySCO corrected blip-up data: saved as a nifti file.

  • HySCO corrected blip-down data: saved as a nifti file.

The HySCO GUI Fig. 2: Illustration of the output of HySCO on a typical SC dMRI dataset. The uncorrected dMRI dataset (here, a b0 image is shown) features susceptibility artifacts manifested as geometric distortions (here: contraction) of the cord in the phase-encoding (anterior-posterior) direction, causing significant misalignment with respect to a reference structural image (see red contour lines). In contrast, the geometric distortion was largely removed in the HySCO-corrected b0 image, greatly improving the overlap with the reference image.

References

Ruthotto, L, Kugel, H, Olesch, J, Fischer, B, Modersitzki, J, Burger, M, and Wolters, C H. Diffeomorphic Susceptibility Artefact Correction of Diffusion-Weighted Magnetic Resonance Images. Physics in Medicine and Biology, 57(18), 5715-5731; 2012.

Ruthotto, L, Mohammadi, S, Heck, C, Modersitzki, J, and Weiskopf, N. HySCO - Hyperelastic Susceptibility Artifact Correction of DTI in SPM. Presented at the Bildverarbeitung fuer die Medizin 2013.

Macdonald, J., Ruthotto, L. Improved Susceptibility Artifact Correction of Echo-Planar MRI using the Alternating Direction Method of Multipliers J Math Imaging Vis 60, 268–282 (2018).

J. Modersitzki: FAIR: Flexible Algorithms for Image Registration. SIAM, Philadelphia, 2009.

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