High-resolution cardiac MRI using partially separable functions and weighted spatial smoothness regularization.

Imaging of cardiac morphology and functions in high spatiotemporal resolution using MRI is a challenging problem due to limited imaging speed and the inherent tradeoff between spatial resolution, temporal resolution, and signal-to-noise ratio (SNR). The partially separable function (PSF) model has been shown to achieve high spatiotemporal resolution but can lead to noisy reconstructions. This paper proposes a method to improve the SNR and reduce artifacts in PSF-based reconstructions through the use of anatomical constraints. These anatomical constraints are obtained from a high-SNR image of composite (k, t)-space data (summed along the time axis) and used to regularize the PSF reconstruction. The method has been evaluated on experimental data of rat hearts to achieve 390 εm in-plane resolution and 15 ms temporal resolution.