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

Synopsis

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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