Carotid far wall characterization using LBP, Laws' Texture Energy and wall variability: A novel class of Atheromatic systems

In this work, we present a Computer Aided Diagnostic (CAD) technique (a class of Atheromatic systems) that classifies the automatically segmented carotid far wall Intima-Media Thickness (IMT) regions along the common carotid artery into symptomatic and asymptomatic classes. We extracted texture feat...

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Bibliographic Details
Main Authors: Acharya, U. Rajendra, S., Vinitha Sree, M., Muthu Rama Krishnan, Saba, Luca, Molinari, Filippo, Shafique, Shoaib, Nicolaides, Andrew, Suri, Jasjit S.
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Asymptomatic
Atherosclerosis
Carotid arteries
Carotid Far Wall
Classifiers
Feature extraction
Laws' Texture Energy
Local Binary Patterns
Symptomatic
Training
Ultrasonic imaging
Ultrasonic variables measurement
Wall Variability
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Summary:In this work, we present a Computer Aided Diagnostic (CAD) technique (a class of Atheromatic systems) that classifies the automatically segmented carotid far wall Intima-Media Thickness (IMT) regions along the common carotid artery into symptomatic and asymptomatic classes. We extracted texture features based on Local Binary Patterns (LBP) and Law's Texture Energy (LTE) and used the significant features to train and test the Support Vector Machine classifier. We developed the classifiers using three-fold stratified cross validation data resampling technique on 342 IMT wall regions. An accuracy of 89.5% was registered. Thus, the proposed technique is accurate, robust, non-invasive, fast, objective, and cost-effective, and hence, will add more value to the existing carotid plaque diagnostics protocol.
ISSN:1094-687X
1558-4615
2694-0604
DOI:10.1109/EMBC.2012.6345964