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Abstract #1597

Rapid Material Characterization For 3D-printed MRI Coils: A Deep Learning Approach

Bahareh Behzadnezhad1,2, Nader Behdad1, and Alan B. McMillan2,3

1Electrical Engineering, University of Wisconsin-Madison, Madison, WI, United States, 2Radiology, University of Wisconsin-Madison, Madison, WI, United States, 3Medical Physics, University of Wisconsin-Madison, Madison, WI, United States

A novel material characterization approach which is based on a microstrip line test fixture paired with deep learning analysis, is presented to optimize the use of additive manufacturing (3D-printing) in constructing the structure of MRI coils with arbitrary 3D geometries. This type of manufacturing is appealing because it can be used to construct geometries that are time-consuming and expensive to make using traditional machining methods. Full-wave electromagnetic simulations are efficient and promising technique to expedite the design process of MRI coils and therefore, it is crucial to include the electrical properties of 3D-printed materials in the electromagnetic simulations because it affects coil performance.

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