Artificial Intelligence and Myocardial Contrast Enhancement Pattern.

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 Rep

authors

Tang F,Bai C,Zhao XX,Yuan WF

doi

10.1007/s11886-020-01306-0

subject

Has Abstract

pub_date

2020-07-07 00:00:00

pages

77

issue

8

eissn

1523-3782

issn

1534-3170

pii

10.1007/s11886-020-01306-0

journal_volume

22

pub_type

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