  Spiral acquisitions are preferred in real-time MRI because of their time
efficiency. A fundamental limitation of spirals is image blurring due to
off-resonance, which degrades image quality significantly at air-tissue
boundaries. Here, we demonstrate a simple CNN-based deblurring method for
spiral real-time MRI of human speech production. We show the CNN-based
deblurring is capable of restoring blurred vocal tract tissue boundaries,
without a need for exam-specific field maps. Deblurring performance is superior
to a current auto-calibrated method, and slightly inferior to ideal
reconstruction with perfect knowledge of the field maps.
