Quantitative Estimation Method for Liver Fibrosis Based on Combination of Rayleigh Distributions
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概要
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Since the clinical diagnosis based on ultrasonic B-mode images is dependent on the skill of the doctor, the realization of a quantitative diagnostic method using ultrasound echo signals is highly required. We have been investigating the quantitative diagnostic technique mainly on hepatic diseases. In this paper, we present a new analysis method using echo signals for the quantitative estimation of liver fibrosis. To quantitatively determine the stage of liver fibrosis, we propose a model in which the probability density function of echo amplitude is expressed as a combination of two Rayleigh distributions. These two Rayleigh distributions correspond to the echo components from the normal and diseased tissues. In addition, using this amplitude distribution model of echo amplitude, we present the estimation method to obtain the amount of fibrous tissue and stage of fibrotic degeneration of the liver from moments about mean of the echo amplitude. Basic examination using clinical images suggest that the quantitative estimation of liver fibrosis based on a combination of Rayleigh distributions is valid.
- 2010-07-25
著者
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Yamaguchi Tadashi
Research Center For Frontier Medical Engineering Chiba University
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Hachiya Hiroyuki
Graduate School Of Science And Engineering Tokyo Institute Of Technology
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Hachiya Hiroyuki
Graduate School of Science and Engineering, Tokyo Institute of Technology, Ookayama, Meguro, Tokyo 152-8552, Japan
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Igarashi Yu
Graduate School of Science and Engineering, Tokyo Institute of Technology, Meguro, Tokyo 152-8552, Japan
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Ezuka Hiroshi
Graduate School of Advanced Integration Science, Chiba University, Inage-ku, Chiba 263-8522, Japan
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Yamaguchi Tadashi
Research Center for Frontier Medical Engineering, Chiba University, Inage-ku, Chiba 263-8522, Japan
関連論文
- Stability of Quantitative Evaluation Method of Liver Fibrosis Using Amplitude Distribution Model of Fibrotic Liver
- Quantitative Estimation Method for Liver Fibrosis Based on Combination of Rayleigh Distributions
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