Imaging Based Symptomatic Classification Using a Combination of Trace Transform, Fuzzy Technique and Multitude of Features

摘要

A statistical (a) Computer Aided Diagnostic (CAD) technique is described for symptomatic versus asymptomatic plaque automated classification of carotid ultrasound images and (b) presents a cardiovascular risk score computation. We demonstrate this for longitudinal Ultrasound, CT, MR modalities and extendable to 3D carotid Ultrasound. The on-line system consists of Atherosclerotic Wall Region estimation using AtheroEdge™ for longitudinal Ultrasound or Athero-CTView™ for CT or Athero-MRView from MR. This greyscale Wall Region is then fed to a feature extraction processor which uses the combination: (a) Higher Order Spectra; (b) Discrete Wavelet Transform (DWT); (c) Texture and (d) Wall Variability. Another combination uses: (a) Local Binary Pattern; (b) Law's Mask Energy and (c) Wall Variability. Another combination uses: (a) Trace Transform; (b) Fuzzy Grayscale Level Co-occurrence Matrix and (c) Wall Variability. The output of the Feature Processor is fed to the Classifier which is trained off-line.