Dynamic arterial spin labeling angiography enables non-invasive visualization of arterial flow patterns, but is often time-consuming to perform. Undersampled radial trajectories help reduce acquisition time, but can result in noise-like aliasing artefacts and reduced spatial fidelity, particularly for a combined angiographic and perfusion golden ratio imaging technique, CAPRIA. An image reconstruction framework leveraging coil information and sparsity in the spatial and temporal frequency domains is presented which reduces aliasing and improves image sharpness in both 2D and 3D data. In addition, scan time reductions up to 10x are shown to be feasible whilst maintaining spatial and temporal information.
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