Abstract #0792

Deep-Learning based Wall Shear Stress Assessments from 3D Aortic Shape

Bharath Ambale Venkatesh¹, Nadjia Kachenoura², Kevin Bouaou², Thomas Dietenbeck², Rithvik Rithvik Swamynathan³, Alban Redheuil², Elie Mousseaux⁴, and Joao A C Lima³

¹Radiology, Johns Hopkins University, Baltimore, MD, United States, ²Sorbonne Université, Paris, France, ³Johns Hopkins University, Baltimore, MD, United States, ⁴Université de Paris, Hôpital Européen Georges Pompidou, Paris, France

Synopsis

We develop deep learning for full aortic wall shear stress assessment using 3D aortic shapes and ascending aortic waveforms as input flow. Technically, this would reduce the acquisition time to less than a minute and the post-processing time to a few seconds.

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