Magnetic resonance imaging (MRI) is a powerful medical imaging modality that is non-invasive and has no ionizing radiation. In computational MRI, we use prior knowledge to inform the design of new acquisition schemes, as well as solve large-scale image reconstruction problems that may consist of millions of unknowns. To efficiently solve these problems, we have developed the Berkeley Advanced Reconstruction Toolbox (BART). BART
is a free and open source image reconstruction framework, available at http://mrirecon.github.io/bart/
. The toolbox contains a multi-dimensional array processing library and implements several reconstruction algorithms for parallel imaging
and compressed sensing. In this talk I will give an overview of MRI, discuss some high-dimensional applications, and show how BART can be used in a daily workflow for research and clinical prototyping.