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Abstract #2342

Model-based self-navigated water/fat decomposition for segmented diffusion-weighted EPI

Yiming Dong1, Malte Riedel2, Kirsten Koolstra3, Matthias J.P. van Osch1, and Peter Börnert1,4
1C.J. Gorter Center for High Field MRI, Department of Radiology, LUMC, Leiden, Netherlands, 2University and ETH Zurich, Zurich, Switzerland, 3Division of Image Processing, Department of Radiology, LUMC, Leiden, Netherlands, 4Philips Research, Hamburg, Germany


Multi-shot EPI readout-approaches provide high spatial resolution at reduced geometric distortions and improved SNR in diffusion weighted imaging (DWI). As a specific challenge, multi-shot acquisition data require corrections for motion-induced, shot-specific phase errors, e.g. using additional navigator signals or appropriate self-navigation. Furthermore, proper fat-suppression is challenging in DWI, especially at B0 critical regions, making the use of chemical-shift encoding interesting. Therefore, an iterative, model-based reconstruction algorithm with self-navigation and water/fat decomposition, is proposed in this work. In-vivo examples in the leg and head-neck regions demonstrate improved water/fat separation as compared to acquisition-navigator approaches, while measurement times can be shortened.

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