Eddy current corrections are essential in preprocessing 4D flow data due to differing offset errors in each flow component leading to spatiotemporal inaccuracies in the velocity vector-field. Current automated optimization methods may require training data, have limited generalizability to different scan protocols, are sensitive to wraparound errors, and do not account for complex spatiotemporal errors. We introduce a self-calibrating method to optimize eddy current corrections and detect wraparound errors by using our recent 4D flow-field disparity signature technique that stochastically encodes the entire spatiotemporal profile of paired vector disparities and show feasibility and generalizability to two different 4D flow protocols.
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