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Abstract #1690

Deep Learning-Based Automatic Segmentation of Non-contrast Coronary Magnetic Resonance Angiography Images

Lu Lin1, Difei Jiang2, Yueting Xiao2, and Yining Wang1
1Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, 2Shukun (Beijing) Technology Co., Ltd, Beijing, China

Synopsis

Keywords: Heart, CardiovascularCoronary Magnetic Resonance Angiography (CMRA) is the only non-invasive coronary artery imaging method without radiation exposure and contrast media, and its application in clinical practice has been increasing. However, image post-processing for clinical diagnosis is time-consuming and requires expertise for radiologists. We proposed a three-dimensional U-Net-based automatic method for CMRA images by transfer learning from a pre-trained model of coronary computed tomography angiography(CCTA) to obtain accurate segmentation of coronary arteries.

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