Abstract #2635

Automated Vessel Segmentation for 2D Phase Contrast MR Using Deep Learning

Ning Jin¹, Maria Monzon², Teodora Chitiboi³, Aaron Pruitt⁴, Daniel Giese², Matthew Tong⁵, and Orlando P Simonetti^5,6,7

¹Cardiovascular MR R&D, Siemens Medical Solutions USA, Inc., Cleveland, OH, United States, ²Siemens Healthcare, Erlangen, Germany, ³Siemens Medical Solutions USA, Inc, Princeton, NJ, United States, ⁴Biomedical Engineering, The Ohio State University, Columbus, OH, United States, ⁵Internal Medicine, The Ohio State University, Columbus, OH, United States, ⁶Davis Heart & Lung Research Institute, The Ohio State University, Columbus, OH, United States, ⁷Radiology, The Ohio State University, Columbus, OH, United States

Phase-contrast (PC) MRI is used to evaluate blood hemodynamics; however, it can be time consuming to process PC-MR data. In this work, we developed a fully automated segmentation algorithm for PC MR images using deep learning (DL). Automated segmentation of aorta and main pulmonary artery from PC MRI scans can be successfully achieved using the DL model.

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