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Abstract #2802

Machine Learning Using the BART Toolbox - Implementation of a Deep Convolutional Neural Network for Denoising

Martin Uecker1,2

1University Medical Center Göttingen, Göttingen, Germany, 2Partner-site Göttingen, DZHK (German Centre for Cardiovascular Research), Göttingen, Germany

Deep convolutional neural networks (DCNNs) tend to outperfom conventional image processing algorithms in recent benchmarks for classifcation, segmentation, denoising, and many other image processing tasks. Here, we show how DCNNs can be implemented using existing building blocks already provided by the BART image reconstruction toolbox. As proof-of-principle we discuss the implementation of an image denoising tool based on a pre-trained DCNN.

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