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Tissue characterization of coronary plaque by kNN classifier with fractal-based features of IVUS RF-signal

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Abstract

We propose a tissue characterization method for coronary plaques by using fractal analysis-based features. Those features are obtained from radiofrequency (RF) signals measured by the intravascular ultrasound (IVUS) method. The IVUS method is used for the diagnosis of the acute coronary syndrome. In the proposed method, the fact that the complexity of the tissue structures is reflected in the RF signals is used. The effectiveness of the proposed method is verified through some experiments by using IVUS RF signals obtained from rabbits and human patients.

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Acknowledgments

The authors would like to thank Prof. T. Hiro of Nihon University, School of Medicine, for providing the IVUS data and for his helpful discussion. Many thanks are also due to Mr. Y. Tanaka for his helpful assistance. This work was supported by the Grant-in-Aid for Scientific Research (B) of the Japan Society for Promotion of Science (JSPS) under the Contract No. 23300086.

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Correspondence to Eiji Uchino.

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Uchino, E., Koga, T., Misawa, H. et al. Tissue characterization of coronary plaque by kNN classifier with fractal-based features of IVUS RF-signal. J Intell Manuf 25, 973–982 (2014). https://doi.org/10.1007/s10845-013-0793-3

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  • DOI: https://doi.org/10.1007/s10845-013-0793-3

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