DocumentCode
1740596
Title
Noninvasive localization of myocardial infarction by means of a 3D heart-model based inverse imaging approach
Author
Li, Guanglin ; He, Bin
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Illinois Univ., Chicago, IL, USA
Volume
2
fYear
2000
fDate
2000
Firstpage
891
Abstract
It is of significance to localize sites of myocardial infarction (MI) noninvasively. The authors have investigated the feasibility of localizing MI sites from body surface ECGs in terms of a heart-model based new inverse solution. A preliminary diagnosis system was developed based on an artificial neural network (ANN) to limit the searching space of the optimization algorithm and to set the initial parameters in the heart simulation model. The optimal heart-model parameters were obtained by minimizing the difference between the observed and model-generated body surface ECGs. The present computer simulation shows promising results indicating that the present approach produces a 100% success rate in localization of an area of acute MI in the left ventricle for cases studied. The present study suggests this approach merits further investigation, and may provide an important alternative to ECG inverse solutions
Keywords
digital simulation; diseases; electrocardiography; inverse problems; medical image processing; neural nets; optimisation; physiological models; 3D heart-model based inverse imaging approach; ECG inverse solutions; artificial neural network; electrodiagnostics; myocardial infarction; noninvasive localization; optimal heart-model parameters; optimization algorithm searching space; preliminary diagnosis system; Artificial neural networks; Cardiac disease; Computational modeling; Computer simulation; Electrocardiography; Heart; Inverse problems; Myocardium; Pathology; Surface reconstruction;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE
Conference_Location
Chicago, IL
ISSN
1094-687X
Print_ISBN
0-7803-6465-1
Type
conf
DOI
10.1109/IEMBS.2000.897862
Filename
897862
Link To Document