MAGO-SP: detection and correction of water-fat swaps in magnitude-only VIBE MRI

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Item Type:	Conference or Workshop Item
Title:	MAGO-SP: detection and correction of water-fat swaps in magnitude-only VIBE MRI
Creators Name:	Graf, Robert, Möller, Hendrik, Starck, Sophie, Atad, Matan, Braun, Philipp, Stelter, Jonathan, Peters, Annette, Krist, Lilian, Willich, Stefan N., Völzke, Henry, Bülow, Robin, Pischon, Tobias, Niendorf, Thoralf, Paetzold, Johannes C., Karampinos, Dimitrios, Rueckert, Daniel and Kirschke, Jan
Abstract:	Volume Interpolated Breath-Hold Examination (VIBE) MRI generates images suitable for water and fat signal composition estimation. While the two-point VIBE provides rapid water-fat-separated images, the six-point VIBE allows estimation of the effective transversal relaxation rate R2* and the proton density fat fraction (PDFF), which are imaging markers for health and disease. Ambiguity during signal reconstruction can lead to water-fat swaps. This shortcoming challenges the application of VIBE-MRI for automated PDFF analyses of largescale clinical data and population studies. This study develops an automated pipeline to detect and correct water-fat swaps in non-contrastenhanced VIBE images. Our three-step pipeline begins with training a segmentation network to classify volumes as “fat-like” or “water-like”, using synthetic water-fat swaps generated by merging fat and water volumes with Perlin noise. Next, a denoising diffusion image-to-image network predicts water volumes as signal priors for correction. Finally, we integrate this prior into a physics-constrained model to recover accurate water and fat signals. Our approach achieves a <1% error rate in water-fat swap detection for a 6-point VIBE. Notably, swaps disproportionately affect individuals in the Underweight and Class 3 Obesity BMI categories. Our correction algorithm ensures accurate solution selection in chemical phase MRIs, enabling reliable PDFF estimation. This forms a solid technical foundation for automated large-scale population imaging analysis.
Keywords:	MRI, Water-Fat MRI, Water-Fat Swaps, Proton Density Fat Fraction
Source:	Lecture Notes in Computer Science
Series Name:	Lecture Notes in Computer Science
Title of Book:	Medical Image Computing and Computer Assisted Intervention - MICCAI 2025
ISSN:	0302-9743
ISBN:	978-3-032-05168-4
Publisher:	Springer
Volume:	15972
Page Range:	328-338
Number of Pages:	11
Date:	20 September 2025
Official Publication:	https://doi.org/10.1007/978-3-032-05169-1_32
Related to:	URL URL Type https://github.com/robert-graf/MAGO-SP Software

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