Abstract:
PURPOSE OF REVIEW:Machine learning (ML) and deep learning (DL) are two important categories of AI algorithms. Nowadays, AI technology has been gradually applied to cardiac magnetic resonance imaging (CMRI), covering the fields of myocardial contrast enhancement (MCE) pattern and automatic ventricular segmentation. This paper mainly discusses the relationship between machine learning and deep learning based on AI and pattern of MCE in CMRI. RECENT FINDINGS:It found that some histogram and GLCM parameters in ML algorithm had significant statistical differences in diagnosis of cardiomyopathy and differentiation of fibrosis and normal myocardial tissue. In the DL algorithm, there was no significant difference between CNN and observers in measuring myocardial fibrosis. The rapid development of texture parameter analysis methods would promote the medical imaging based on AI into a new era. Histogram and GLCM parameters are the research hotspot of unsupervised learning of MCE images. CNN has a great advantage in automatically identifying and quantifying myocardial fibrosis reflected by LGE images.
journal_name
Curr Cardiol Repjournal_title
Current cardiology reportsauthors
Tang F,Bai C,Zhao XX,Yuan WFdoi
10.1007/s11886-020-01306-0subject
Has Abstractpub_date
2020-07-07 00:00:00pages
77issue
8eissn
1523-3782issn
1534-3170pii
10.1007/s11886-020-01306-0journal_volume
22pub_type
杂志文章,评审abstract::Dual antiplatelet therapy with aspirin and clopidogrel is a well-established standard of care for patients with acute coronary syndromes. Whether there are other drug strategies or therapies that will achieve fewer ischemic events, and at the same time be associated with fewer bleeding complications, is a question rec...
journal_title:Current cardiology reports
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journal_title:Current cardiology reports
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journal_title:Current cardiology reports
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pub_type: 杂志文章,评审
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pub_type: 杂志文章,评审
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journal_title:Current cardiology reports
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更新日期:2007-09-01 00:00:00
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