Abstract #0698

Denoising 4D-Flow using Self-Supervised Deep Learning and its effect on test-rest reproducibility

Brock W Jolicoeur¹, Leonardo A Rivera-Rivera¹, Grant S Roberts¹, Laura Eisenmenger², and Kevin M Johnson¹

¹Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, ²Radiology, University of Wisconsin-Madison, Madison, WI, United States

Synopsis

Keywords: Flow, Blood vessels, Machine Learning/Artificial IntelligenceThrough a self-supervised deep learning denoising algorithm, more precise cerebrovascular measurements of flow, maximum fluid velocity, and vessel cross-sectional area were obtained from undersampled neurovascular 4D-Flow MRI data. This algorithm was applied to back-to-back scans to illustrate its effectiveness in reducing measurement variance.

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