Improving distortion correction for isotropic high‐resolution 3D diffusion MRI by optimizing Jacobian modulation

Liu, Simin; Xiong, Yuhui; Dai, Erpeng; Zhang, Jieying; Guo, Hua

doi:10.1002/mrm.28884

Cited by 8 publications

(8 citation statements)

References 40 publications

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“…Finally, the B 0 field-mapping approach only corrects for EPI image deformation, but not intensity differences. However, the latter can have a substantial effect, especially in high-resolution imaging ( Liu et al., 2021 ). Intensity correction is not typically performed as part of the B 0 field mapping distortion correction approach, and was not used in this study, because it is often poorly conditioned.…”

Section: Discussionmentioning

confidence: 99%

Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T

et al. 2023

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Section: Discussionmentioning

confidence: 99%

Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T

et al. 2023

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“…More details regarding intensity corrections using Jacobian modulation used in this paper can be found in the Text S3 in Appendix S1. In this work, the optimized Jacobian modulation method is used based on the recent work, 27 and the corrected images can be obtained by the following Equation:

{I}_{\mathrm{undis}}\left(x,y\right)=\frac{2{I}_{\mathrm{dis}\ \mathrm{u}p}\left(x,y+u\left(x,y\right)\right)\ast {I}_{\mathrm{dis}\ \mathrm{down}}\left(x,y-u\left(x,y\right)\right)}{I_{\mathrm{dis}\ \mathrm{u}\mathrm{p}}\left(x,y+u\left(x,y\right)\right)+{I}_{\mathrm{dis}\ \mathrm{down}}\left(x,y-u\left(x,y\right)\right)}.

…”

Section: Methodsmentioning

confidence: 99%

Section: Geometric and Intensity Correction Based On Dlrpg-net Learne...mentioning

confidence: 99%

Unsupervised cycle‐consistent network using restricted subspace field map for removing susceptibility artifacts in EPI

Bao¹,

Xie

Otikovs

et al. 2023

Magnetic Resonance in Med

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Purpose: To design an unsupervised deep neural model for correcting susceptibility artifacts in single-shot Echo Planar Imaging (EPI) and evaluate the model for preclinical and clinical applications. Methods:This work proposes an unsupervised cycle-consistent model based on the restricted subspace field map to take advantage of both the deep learning (DL) and the reverse polarity-gradient (RPG) method for single-shot EPI.The proposed model consists of three main components: (1) DLRPG neural network (DLRPG-net) to obtain field maps based on a pair of images acquired with reversed phase encoding; (2) spin physical model-based modules to obtain the corrected undistorted images based on the learned field map; and (3) cycle-consistency loss between the input images and back-calculated images from each cycle is explored for network training. In addition, the field maps generated by DLRPG-net belong to a restricted subspace, which is a span of predefined cubic splines to ensure the smoothness of the field maps and avoid blurring in the corrected images. This new method is trained and validated on both preclinical and clinical datasets for diffusion MRI. Results:The proposed network could effectively generate smooth field maps and correct susceptibility artifacts in single-shot EPI. Simulated and in vivo preclinical/clinical experiments demonstrated that our method outperforms the state-of-the-art susceptibility artifact correction methods. Furthermore, the ablation experiments of the cycle-consistent network and the restricted subspace in generating field maps did show the advantages of DLRPG-net. Conclusion:The proposed method (DLRPG-net) can effectively correct susceptibility artifacts for preclinical and clinical single-shot EPI sequences.

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“…Then, eddy current effects are corrected using the eddy function 35 from the FSL software package (v6.0.3) 36 . B 0 inhomogeneity–induced distortions are corrected using the B 0 field map estimated from the FSL's topup function 37 and an optimized Jacobian modulation matrix 38 …”

Section: Methodsmentioning

confidence: 99%

“…36 B 0 inhomogeneity-induced distortions are corrected using the B 0 field map estimated from the FSL's topup function 37 and an optimized Jacobian modulation matrix. 38…”

Section: Other Artifact Correctionmentioning

confidence: 99%

Three‐dimensional diffusion MRI using simultaneous multislab with blipped‐CAIPI in a 4D k‐space framework

Liu

Zhang

Shi

et al. 2023

Magnetic Resonance in Med

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Purpose To develop an efficient simultaneous multislab imaging method with blipped‐controlled aliasing in parallel imaging (blipped‐SMSlab) in a 4D k‐space framework, and to demonstrate its efficacy in high‐resolution diffusion MRI (dMRI). Theory and Methods First, the SMSlab 4D k‐space signal expression is formulated, and the phase interferences from intraslab and interslab encodings on the same physical z‐axis are analyzed. Then, the blipped‐SMSlab dMRI sequence is designed, with blipped–controlled aliasing in parallel imaging (blipped‐CAIPI) gradients for interslab encoding, and a 2D multiband accelerated navigator for inter‐kz‐shot phase correction. Third, strategies are developed to remove the phase interferences, by RF phase modulation and/or phase correction during reconstruction, thus decoupling intraslab and interslab encodings that are otherwise entangled. In vivo experiments are performed to validate the blipped‐SMSlab method and preliminarily evaluate its performance in high‐resolution dMRI compared with traditional 2D imaging. Results In the 4D k‐space framework, interslab and intraslab phase interferences of blipped‐SMSlab are successfully removed using the proposed strategies. Compared with non–CAIPI sampling, the blipped‐SMSlab acquisition reduces the g‐factor and g‐factor‐related SNR penalty by about 12%. In addition, in vivo experiments show the SNR advantage of blipped‐SMSlab dMRI over traditional 2D dMRI for 1.3‐mm and 1.0‐mm isotropic resolution imaging with matched acquisition time. Conclusion Removing interslab and intraslab phase interferences enables SMSlab dMRI with blipped‐CAIPI in a 4D k‐space framework. The proposed blipped‐SMSlab dMRI is demonstrated to be more SNR‐efficient than 2D dMRI and thus capable of high‐quality, high‐resolution fiber orientation detection.

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Improving distortion correction for isotropic high‐resolution 3D diffusion MRI by optimizing Jacobian modulation

Cited by 8 publications

References 40 publications

Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T

Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T

Unsupervised cycle‐consistent network using restricted subspace field map for removing susceptibility artifacts in EPI

Three‐dimensional diffusion MRI using simultaneous multislab with blipped‐CAIPI in a 4D k‐space framework

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