ArticleMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention2026
Accelerated Free-Breathing 5D Multi-Echo Respiratory Motion-Resolved R2*, PDFF, and QSM Using Novel Composite Total Variation.
Article in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
We introduce a novel composite total variation (TV) and its solution algorithm with their application to multi-echo, respiratory motion-resolved 5D (3D space + 1D respiratory motion + 1D echo signal evolution) compressed sensing (CS) abdominal MR image reconstruction. The proposed formalism ensures a sparse representation between multi-echo images with varying contrast-a vital feature that needs to be preserved-making it highly suitable for applications in multi-dimensional computational/quantitative imaging. The key idea of the proposed composite TV and its formal definition were inspired by the observation that the spatial gradient of difference images in multi-echo MRI appears sparse. Throughout extensive experiments on a small number of healthy volunteers, we have demonstrated improved performance of the proposed method in 5D motion-resolved CS reconstruction of multi-echo MRI data compared to the state-of-the-art method. We have also demonstrated improved performance of the proposed method in quantitative tissue parameter mapping (such as R2*, proton density fat fraction, and quantitative susceptibility mapping) across a wide range of undersampling factors. In conclusion, the proposed method enables vastly accelerated motion-resolved multi-echo CS-MRI minimally impacting the quantification of downstream tissue parameters.
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