NDLI: Challenges in Atherosclerotic Plaque Characterization With Intravascular Ultrasound (IVUS): From Data Collection to Classification

Content Provider	IEEE Xplore Digital Library
Author	Katouzian, A. Sathyanarayana, S. Baseri, B. Konofagou, E.E. Carlier, S.
Copyright Year	1997
Abstract	In vivo plaque characterization is an important research field in interventional cardiology. We will study the realistic challenges to this goal by deploying 40 MHz single-element, mechanically rotating transducers. The intrinsic variability among the transducers' spectral parameters as well as tissue signals will be demonstrated. Subsequently, we will show that global data normalization is not suited for data calibration, due to the aforementioned variations as well as the stringent characteristics of spectral features. We will describe the sensitivity of an existing feature extraction algorithm based on eight spectral signatures (integrated backscatter coefficient, slope, midband-fit (MBF), intercept, and maximum and minimum powers and their relative frequencies) to a number of factors, such as the window size and order of the autoregressive (AR) model. It will be further demonstrated that the variations in the transducer's spectral parameters (i.e., center frequency and bandwidth) cause inconsistencies among extracted features. In this paper, two fundamental questions are addressed: 1) what is the best reliable way to extract the most informative features? and 2) which classification algorithm is the most appropriate for this problem? We will present a full-spectrum analysis as an alternative to the eight-feature approach. For the first time, different classification algorithms, such as k -nearest neighbors (k-NN) and linear Fisher, will be employed and their performances quantified. Finally, we will explore the reliability of the training dataset and the complexity of the recognition algorithm and illustrate that these two aspects can highly impact the accuracy of the end result, which has not been considered until now.
Sponsorship	IEEE Engineering in Medicine and Biology Society IEEE Computer Society
Starting Page	315
Ending Page	327
Page Count	13
File Size	1212023
File Format	PDF
ISSN	10897771
Volume Number	12
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Ultrasonic imaging Ultrasonic transducers Feature extraction Frequency Classification algorithms In vivo Cardiology Calibration Backscatter Bandwidth tissue characterization intravascular ultrasound spectral analysis Tissue Characterization Feature Extraction Intravascular Ultrasound Spectral Analysis
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications Biotechnology

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