Analysis of Coronary Angiography Video Interpolation Methods to Reduce X-ray Exposure Frequency Based on Deep Learning
作者机构：The Future LaboratoryTsinghua UniversityChengfu Road 160HaidianBeijingChina Center for CardiologyBeijing Anzhen HospitalCapital Medical UniversityAnzhen RoadBeijingChina The First Affi liated Hospital of Zhengzhou UniversityJianshe East RoadErqi DistrictZhengzhouChina
出 版 物：《Cardiovascular Innovations and Applications》 (心血管创新与应用（英文）)
年 卷 期：2021年第6卷第3期
页 面：17-24页
学科分类：1002[医学-临床医学] 100201[医学-内科学(含：心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 10[医学]
主 题：coronary angiography video interpolation deep learning X-ray exposure frequency
摘 要：Cardiac coronary angiography is a major technique that assists physicians during interventional heart *** X-ray irradiation,the physician injects a contrast agent through a catheter and determines the coronary arteries’state in real ***,to obtain a more accurate state of the coronary arteries,physicians need to increase the fre-quency and intensity of X-ray exposure,which will inevitably increase the potential for harm to both the patient and the *** the work reported here,we use advanced deep learning algorithms to fi nd a method of frame interpola-tion for coronary angiography videos that reduces the frequency of X-ray exposure by reducing the frame rate of the coronary angiography video,thereby reducing X-ray-induced damage to *** established a new coronary angiography image group dataset containing 95,039 groups of images extracted from 31 *** group includes three consecutive images,which are used to train the video interpolation network *** apply six popular frame interpolation methods to this dataset to confi rm that the video frame interpolation technology can reduce the video frame rate and reduce exposure of physicians to X-rays.
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