Quantitative parameter maps offer valuable information about various tissue attributes, which are early markers for many neurological disorders. However the long acquisition time of the associated image time series puts a restriction on the achievable spatial resolution. In this work, we introduce a novel framework, which exploits the exponential nature of the time profiles at every pixel and spatial smoothness of the exponential parameters to recover the images from highly under-sampled measurements. Our preliminary results clearly demonstrate the potential of the proposed algorithm.
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