Unified Motion Correction and Reconstruction for Accelerated Zero Echo Time MRI

Zero echo time (ZTE) MRI is near-silent, but dead time gaps, head motion, and undersampling jointly degrade reconstruction. To develop an accelerated ZTE MRI reconstruction framework that jointly estimates the 3D image and rigid-motion parameters, this work introduces Energy-based Motion Correction (EnMoCo), a regularized maximum a posteriori (MAP) formulation that also compensates for missing k-space center data and angular undersampling artifacts. Solved by alternating between k-space rigid-motion updates and conjugate-gradient data-consistency updates, the framework incorporates regularization via a pre-trained Multi-Scale Energy-based model (MuSE) implemented in a data-efficient 2.5D form. Evaluations on simulated and in vivo 3D ZTE data, spanning dead time gaps of 1.5 to 5 samples, rotations up to 17 degrees and translations up to 10 mm, demonstrate that EnMoCo significantly improves PSNR and SSIM relative to CG-SENSE and Autofocusing baselines (achieving roughly 10 to 15 dB higher PSNR for gaps >= 3.5) while reducing motion blur and tissue contrast inconsistencies.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-11-03
DOI
https://doi.org/10.48550/arxiv.2611.05169
Primary Topic
Advanced MRI Techniques and Applications
Type
preprint
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preprint

Unified Motion Correction and Reconstruction for Accelerated Zero Echo Time MRI

James H. Holmes, Mathews Jacob, Curtis A. Corum, Yan Chen
arXiv (Cornell University)
Advanced MRI Techniques and Applications
preprint

Unified Motion Correction and Reconstruction for Accelerated Zero Echo Time MRI

James H. Holmes, Mathews Jacob, Curtis A. Corum, Yan Chen
preprint en

Abstract

Zero echo time (ZTE) MRI is near-silent, but dead time gaps, head motion, and undersampling jointly degrade reconstruction. To develop an accelerated ZTE MRI reconstruction framework that jointly estimates the 3D image and rigid-motion parameters, this work introduces Energy-based Motion Correction (EnMoCo), a regularized maximum a posteriori (MAP) formulation that also compensates for missing k-space center data and angular undersampling artifacts. Solved by alternating between k-space rigid-motion updates and conjugate-gradient data-consistency updates, the framework incorporates regularization via a pre-trained Multi-Scale Energy-based model (MuSE) implemented in a data-efficient 2.5D form. Evaluations on simulated and in vivo 3D ZTE data, spanning dead time gaps of 1.5 to 5 samples, rotations up to 17 degrees and translations up to 10 mm, demonstrate that EnMoCo significantly improves PSNR and SSIM relative to CG-SENSE and Autofocusing baselines (achieving roughly 10 to 15 dB higher PSNR for gaps >= 3.5) while reducing motion blur and tissue contrast inconsistencies.

arXiv (Cornell University)
Advanced MRI Techniques and Applications
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Unified Motion Correction and Reconstruction for Accelerated Zero Echo Time MRI — James H. Holmes, Mathews Jacob, et al. · arXiv (Cornell University) (2026) | TGRS Research Map | TGRS