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Abstract #3465

Predicting Breath-Hold Liver Diffusion MRI from Free-Breathing Data using a Convolutional Neural Network (CNN)

Emmanuelle M. M. Weber1, Xucheng Zhu2, Patrick Koon2, Anja Brau2, Shreyas Vasanawala1, and Jennifer A. McNab1
1Stanford, Stanford, CA, United States, 2GE Healthcare, Menlo Park, CA, United States


To reduce artifacts in free breathing single-shot diffusion MRI of the liver, UNet based convolutional neural networks were trained to predict breath-hold data from free-breathing data using: 1) simulated data based on a digital phantom and 2) 31 scans of a healthy volunteer. The developed networks successfully reduced motion induced artifacts in DWI images.

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