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Abstract #0453

Voxel-wise Tracking of Grid Tagged Cardiac Images using a Neural Network Trained with Synthetic Data

Michael Loecher1,2, Luigi E Perotti3, and Daniel B Ennis1,2,4,5
1Radiology, Stanford University, Stanford, CA, United States, 2Radiology, Veterans Affairs Health Care System, Palo Alto, CA, United States, 3Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL, United States, 4Maternal & Child Health Research Institute, Stanford University, Stanford, CA, United States, 5Cardiovascular Institute, Stanford University, Stanford, CA, United States

This work introduces a neural network for tracking myocardial motion in cine grid tagged MR images on a voxel-wise basis. This is achieved with the use a synthetic training dataset that includes comprehensive motion patterns. Synthetic training allows for a known ground truth motion to be included in training. The network was tested against a previous network that tracked only tag line intersections. Displacements and strain maps were generated and compared. The voxel tracking network shows qualitatively better spatial localization of strain, and better radial strain values compared to tracking only tag lines.

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