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Abstract #4641

VAR-NAV: Motion-resolved 4D MRI using vision-assisted reference auto-navigation

Victor Murray1 and Ricardo Otazo1,2
1Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York City, NY, United States, 2Department of Radiology, Memorial Sloan Kettering Cancer Center, New York City, NY, United States

Synopsis

Keywords: Motion Correction, Motion Correction

Motivation: Motion navigation with improved data efficiency and robustness is still needed for free-breathing MRI.

Goal(s): To develop VAR-NAV, a new 2D auto-navigation technique with 100% data efficiency for stack-of-stars acquisitions.

Approach: VAR-NAV directly estimates the position of the liver dome using 2D projection images and AM-FM demodulation. Results can be corrected retrospectively, like in soccer video assistant referee (VAR). VAR-NAV is used to sort continuously acquired data and reconstruct motion-resolved 4D images.

Results: VAR-NAV outperforms conventional 1D PCA-based navigation and does not require additional acquisition as in previous 2D navigation techniques, offering an efficient and accurate method for clinical 4D MRI.

Impact: VAR-NAV estimates a motion signal that represents displacements on 2D images, outperforming conventional PCA-based 1D navigation. No extra navigation data are required, and results can be retrospectively analyzed like in soccer video-assisted-referee (VAR). VAR-NAV promises to improve clinical 4D MRI.

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