{"title":"人工智能在心脏 CT 中的研究进展和应用","authors":"Li-Miao Zou, Ke-Ting Xu, Yi-Ning Wang","doi":"10.1016/j.metrad.2024.100114","DOIUrl":null,"url":null,"abstract":"<div><div>Coronary artery disease (CAD) remains the leading cause of morbidity and mortality globally. The recent years have witnessed a steep increase in the number of cardiac CT examinations, including coronary CT angiography (CCTA) and non-contrast ECG-gated cardiac CT, which put a heavy load on the radiologists. Artificial intelligence (AI), which aims to automate tasks that resembles human intelligence, presents itself as a promising solution. AI has played an increasingly important role in the field of cardiac CT, from advanced image reconstruction to coronary stenosis and plaque analysis, predicting flow, and potentially better risk stratification and event prediction. In this review, we aim to summarize state-of-the-art AI approaches applied to cardiac CT and their future implications.</div></div>","PeriodicalId":100921,"journal":{"name":"Meta-Radiology","volume":"2 4","pages":"Article 100114"},"PeriodicalIF":0.0000,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research advances and applications of artificial intelligence in cardiac CT\",\"authors\":\"Li-Miao Zou, Ke-Ting Xu, Yi-Ning Wang\",\"doi\":\"10.1016/j.metrad.2024.100114\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Coronary artery disease (CAD) remains the leading cause of morbidity and mortality globally. The recent years have witnessed a steep increase in the number of cardiac CT examinations, including coronary CT angiography (CCTA) and non-contrast ECG-gated cardiac CT, which put a heavy load on the radiologists. Artificial intelligence (AI), which aims to automate tasks that resembles human intelligence, presents itself as a promising solution. AI has played an increasingly important role in the field of cardiac CT, from advanced image reconstruction to coronary stenosis and plaque analysis, predicting flow, and potentially better risk stratification and event prediction. In this review, we aim to summarize state-of-the-art AI approaches applied to cardiac CT and their future implications.</div></div>\",\"PeriodicalId\":100921,\"journal\":{\"name\":\"Meta-Radiology\",\"volume\":\"2 4\",\"pages\":\"Article 100114\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Meta-Radiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2950162824000687\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Meta-Radiology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2950162824000687","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research advances and applications of artificial intelligence in cardiac CT
Coronary artery disease (CAD) remains the leading cause of morbidity and mortality globally. The recent years have witnessed a steep increase in the number of cardiac CT examinations, including coronary CT angiography (CCTA) and non-contrast ECG-gated cardiac CT, which put a heavy load on the radiologists. Artificial intelligence (AI), which aims to automate tasks that resembles human intelligence, presents itself as a promising solution. AI has played an increasingly important role in the field of cardiac CT, from advanced image reconstruction to coronary stenosis and plaque analysis, predicting flow, and potentially better risk stratification and event prediction. In this review, we aim to summarize state-of-the-art AI approaches applied to cardiac CT and their future implications.