We present an approach for improving the phase variation representation of complex-valued dynamic MRI temperature mapping. Our technique utilizes phase information to better recover signal loss caused by susceptibility gradients and generate finer representations of dynamic phases variation. Results from numerical and hybrid simulation show that promising improvements in image resolution, susceptibility artifact reduction and phase variation representation can be achieved using our complex-valued super-resolution MRI scheme.
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