Abstract #1756

Using data-driven image priors for image reconstruction with BART

Guanxiong Luo¹, Moritz Blumenthal¹, and Martin Uecker^1,2

¹Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Germany, Göttingen, Germany, ²Campus Institute Data Science (CIDAS), University of Göttingen, Germany, Göttingen, Germany

The application of deep learning has is a new paradigm for MR image reconstruction. Here, we demonstrate how to incorporate trained neural networks into pipelines using reconstruction operators already provided by the BART toolbox. As a proof of concept, we demonstrate how to incorporate a deep image prior trained via TensorFlow into reconstruction within BART's framework.

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