Analysis of myocardial infarction in CMR images using hybrid level set based segmentation and regional ventricle contractility analysis

被引：0

作者：

Muthulakshmi, M. ^{[1
]}

Kavitha, G. ^{[2
]}

机构：

[1] Amrita Vishwa Vidyapeetham, Dept Elect & Commun Engn, Amrita Sch Engn Chennai, Chennai, Tamil Nadu, India

[2] Anna Univ, Dept Elect Engn, MIT Campus, Chennai, Tamil Nadu, India

来源：

2022 SECOND INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRICAL, COMPUTING, COMMUNICATION AND SUSTAINABLE TECHNOLOGIES (ICAECT) | 2022年

关键词：

Myocardial infarction; hybrid level set; cardiac wall motion; clinical LV indices; CMR images; HEART;

D O I：

10.1109/ICAECT54875.2022.9807938

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The assessment of left ventricle ( LV) wall motion plays a major role in the diagnosis of myocardial infarction (MI). The aim of this work is to study regional contractility of LV in MI and normal subjects using magnetic resonance images. The segmentation of ventricular cavity is performed with correntropy based local bias field corrected image fitting (CELBIF) method. Myocardial contraction over a cardiac cycle is estimated for each sector based on Hausdorff distance and wall motion score index. The results show that CELBIF algorithm yields higher value for Dice coefficient (0.92) than LBIF method. The tracking of LV shows an increase in ventricular volume in infarcted subjects for entire cardiac cycle. Lower contraction is observed in infarcted LV cavities due to damage in myocardium sectors. The ventricular tracking and clinical indices detect abnormal cardiac behavior in MI subjects. The regional contractility analysis aids the identification of infarcted myocardial segment.

引用

页数：5

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