Detection of Myocardial Perfusion Defects Using First Pass Perfusion Cardiac MRI Data

被引：0
|
作者：
Kruzick, Stephen [1 ]
Mengshoel, Ole [1 ]
Menon, Prahlad G. [1 ]
机构：
[1] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
来源：
Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications | 2014年 / 8641卷
关键词：
cardiac magnetic resonance imaging; coronary heart disease; classification; Dice index; Gaussian naive Bayes; myocardium; perfusion;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
First pass perfusion cardiac magnetic resonance imaging (FPP-CMR) presents a non-invasive method of detecting restricted blood flow to the myocardium, heart muscle tissue, early in development of coronary heart disease. This paper proposes simple classification methods applied to FPP-CMR data to detect regions of poor perfusion. Preliminary results show correspondence to regions of scar tissue detected from thresholding of late Gadolinium enhancement CMR imaging.
引用
收藏
页码：248 / 254
页数：7
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