Abstract #4204

MRI acceleration using correlation imaging with tissue boundary sparsity

Yu Y. Li¹

¹Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States

In MRI data acquisition, gradient encoding introduces a non-uniform distribution of tissue contrast and boundary information in k-space. As a result, data correlation increases with tissue boundary sparsity from the center to the outer k-space. The presented work investigates a new approach to accelerating MRI by taking advantage of non-uniform k-space data correlation. In this approach, k-space data are collected and reconstructed in a region-by-region fashion using a previously developed high-speed imaging framework, "correlation imaging"^1,2. It is demonstrated that region-by-region correlation imaging can introduce a gain over parallel imaging in imaging acceleration by utilizing more information.

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