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DSA processing is not applied to the coronary artery because heavy artifacts will be generated in DSA images by heart beats and breathing of the patient. However, DSA images of coronary artery contribute to the accuracy of diagnosis and elucidating new pathogenesis of coronary artery diseases. On the other hand, deep learning techniques have been improved and shown to have a high performance. The purpose of this study was to develop a DSA method available for coronary arteries using deep learning techniques.

Development of the DSA Method for Coronary Angiography Using Deep Learning Techniques