Characterizing the location and extent of myocardial infarctions with inverse ECG modeling and spatiotemporal regularization
Myocardial infarction (MI) is among the leading causes of death in the United States. It is
imperative to identify and characterize MIs for timely delivery of life-saving medical …
imperative to identify and characterize MIs for timely delivery of life-saving medical …
Using inverse electrocardiography to image myocardial infarction—reflecting on the 2007 PhysioNet/Computers in Cardiology Challenge
The goal of the 2007 PhysioNet/Computers in Cardiology Challenge was to try to establish
how well it is possible to characterize the location and extent of old myocardial infarcts using …
how well it is possible to characterize the location and extent of old myocardial infarcts using …
Neural network classification of body surface potential contour map to detect myocardial infarction location
S Sabouri, H SadAbadi… - 2010 Computing in …, 2010 - ieeexplore.ieee.org
Neural network classification of body surface potential contour map to detect myocardial
infarction location Page 1 Neural Network Classification of Body Surface Potential Contour Map …
infarction location Page 1 Neural Network Classification of Body Surface Potential Contour Map …
Rule-based Method for Extent and Localization of Myocardial Infarction by Extracted Features of ECG Signals using Body Surface Potential Map Data
N Safdarian, NJ Dabanloo, SA Matini… - Journal of Medical …, 2013 - journals.lww.com
In this study, a method for determining the location and extent of myocardial infarction using
Body Surface Potential Map data of PhysioNet challenge 2007 database is presented. This …
Body Surface Potential Map data of PhysioNet challenge 2007 database is presented. This …
New detection method based on ECG signal features to determine localization and extent of myocardial infarction using Body Surface Potential Map data
N Safdarian, NJ Dabanloo… - 2012 Computing in …, 2012 - ieeexplore.ieee.org
In this study, a method for determining the location and extent of myocardial infarction using
BSPM data that was obtained from PhysioNet challenge 2007 database has been …
BSPM data that was obtained from PhysioNet challenge 2007 database has been …
Using inverse electrocardiography to image myocardial infarction-reflecting on the 2007 PhysioNet/Computers in Cardiology Challenge
FD Beng, GS Wagner - Journal of Electrocardiology, 2008 - search.proquest.com
The goal of the 2007 PhysioNet/Computers in Cardiology Challenge was to try to establish
how well it is possible to characterize the location and extent of old myocardial infarcts using …
how well it is possible to characterize the location and extent of old myocardial infarcts using …
[PDF][PDF] The detection method to determine localization and extent of myocardial infarction: A literature review
A Tarar, SN Jaiswal - 2018 - academia.edu
Cardiovascular diseases is very important to detect as early as possible because it leads to
death in the world, and Myocardial Infarction (MI) is very dangerous one among those …
death in the world, and Myocardial Infarction (MI) is very dangerous one among those …
Rule Based Method for Extent and Localization Detection of Myocardial Infarction by Extracted Features of ECG Signals Using Body Surface Potential Map Data
NJ Dabanloo, SA Matini, AM Nasrabadi - Journal of Medical Signals …, 2013 - jmss.mui.ac.ir
In this study, a method for determining the location and extent of myocardial infarction using
Body Surface Potential Map data that is obtained from PhysioNet challenge 2007 database …
Body Surface Potential Map data that is obtained from PhysioNet challenge 2007 database …
[引用][C] Rule Based Method for Extent and Localization Detection of Myocardial Infarction by Extracted Features of ECG Signals Using Body Surface Potential Map Data
N Jafarnia Dabanloo, SA Matini, AM Nasrabadi - Journal of Medical Signals and …, 2013