Advanced compute-based methods for quantitative image acquisition and reconstruction

The availability of inexpensive GPU-based compute has opened the door to new quantitative model-based strategies for the acquisition and the reconstruction of highly-undersampled imaging data. We have been developing neural network deep learning based approaches such as AUTOMAP and other DRNs to leverage scalable-compute and signficiantly deburden the need for precision hardware.