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Abstract #0083

Novel Self-calibrating 4D Flow-Field Signature Technique to Simultaneously Optimize Eddy Current Corrections and Detect Wraparound Errors

Thara Nallamothu1,2, Haben Berhane1,2, Liliana Ma1, Justin Baraboo1,2, Daniel C. Lee3, Daniel Kim1, Phillip Greenland4, Michael Markl1,2, Rod Passman3, and Mohammed S.M. Elbaz1
1Radiology, Northwestern University, Chicago, IL, United States, 2Biomedical Engineering, Northwestern University, Chicago, IL, United States, 3Medicine (Cardiology), Northwestern University, Chicago, IL, United States, 4Preventative Medicine, Northwestern University, Chicago, IL, United States


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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