Laplacian pyramid based data fusion for high resolution dynamic MRI

Dynamic contrast-enhanced (DCE) MRI is useful for tumor diagnosis and treatment. In DCE, there is a tradeoff between the spatial and temporal resolutions. Improving the spatial resolution while preserving the temporal dynamics is essential for better diagnosis/treatment. We present a method (LAPFUD) for enhancing the spatial frequency without compromising on temporal resolution. LAPFUD combines information from a static high-resolution image acquired at baseline, with each low-resolution frame. By making local decisions it preserves details from both inputs without changing the temporal behavior. Experiments show that LAPFUD provides superior performance (spatially and temporally) compared to the commonly used keyhole method.