Document Detail


Detecting variability of internal carotid arterial Doppler signals by Lyapunov exponents.
MedLine Citation:
PMID:  15564113     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The new method presented in this study was directly based on the consideration that internal carotid arterial Doppler signals are chaotic signals. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. Multilayer perceptron neural network (MLPNN) architecture was formulated and used as a basis for detecting variabilities such as stenosis and occlusion in the physical state of internal carotid arterial Doppler signals. The computed Lyapunov exponents of the internal carotid arterial Doppler signals were used as inputs of the MLPNN. Receiver operating characteristic (ROC) curve was used to assess the performance of the detection process. The internal carotid arterial Doppler signals were classified with the accuracy varying from 94.87% to 97.44%. The results confirmed that the proposed MLPNN trained with Levenberg-Marquardt algorithm has potential in detecting stenosis and occlusion in internal carotid arteries.
Authors:
Inan Güler; Elif Derya Ubeyli
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Publication Detail:
Type:  Clinical Trial; Controlled Clinical Trial; Journal Article; Research Support, Non-U.S. Gov't; Validation Studies    
Journal Detail:
Title:  Medical engineering & physics     Volume:  26     ISSN:  1350-4533     ISO Abbreviation:  Med Eng Phys     Publication Date:  2004 Nov 
Date Detail:
Created Date:  2004-11-26     Completed Date:  2005-04-21     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  9422753     Medline TA:  Med Eng Phys     Country:  England    
Other Details:
Languages:  eng     Pagination:  763-71     Citation Subset:  IM    
Affiliation:
Department of Electronics and Computer Education, Faculty of Technical Education, Gazi University, Teknikokullar, 06500 Ankara, Turkey. iguler@gazi.edu.tr
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MeSH Terms
Descriptor/Qualifier:
Adolescent
Adult
Aged
Algorithms*
Artificial Intelligence*
Carotid Artery Thrombosis / ultrasonography*
Carotid Artery, Internal / ultrasonography*
Carotid Stenosis / ultrasonography*
Female
Humans
Image Interpretation, Computer-Assisted / methods*
Male
Middle Aged
Reproducibility of Results
Sensitivity and Specificity
Ultrasonography, Doppler / methods*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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