Statistical tissue characterization of coronary plaque by ASSOM using intravascular ultrasound method

  • Authors:

  • Ryosuke Kubota;Mami Kunihiro;Noriaki Suetake;Eiji Uchino;Genta Hashimoto;Takafumi Hiro;Masunori Matsuzaki

  • Affiliations:

  • Ube National College of Technology, Department of Intelligent System Engineering, Ube, Japan;Yamaguchi University, Graduate School of Science and Engineering, Yamaguchi, Japan;Yamaguchi University, Graduate School of Science and Engineering, Yamaguchi, Japan;Yamaguchi University, Graduate School of Science and Engineering, Yamaguchi, Japan;Yamaguchi University, Graduate School of Medicine, Ube, Japan;Yamaguchi University, Graduate School of Medicine, Ube, Japan;Yamaguchi University, Graduate School of Medicine, Ube, Japan

  • Venue:
  • ICOSSSE'08 Proceedings of the 7th WSEAS international conference on System science and simulation in engineering
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

Tissue characterization of plaque is very important for a diagnosis of the acute coronary syndromes. The conventional methods however can not perform a good characterization, because the features employed for characterization are not particular for each tissue. In this paper, we propose a novel tissue characterization method by using an adaptive subspace self-organizing map (ASSOM). ASSOM can produce various features from an intravascular ultrasound (IVUS) radiofrequency signal. The acquired features are suitable for the tissue characterization, because the overlap of the distributions of the acquired features is much smaller than the one, e.g., by an integrated backscatter (IB) analysis or by a traditional Fourier spectrum analysis. A tissue is characterized by using the statistical information of the features acquired by ASSOM. Through the application to the tissue characterization of the real IVUS signal, the performance of the proposed method has been verified by comparing it with the conventional methods.