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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 Simonetti5,6,7
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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