Characterization of Renal Stones from Ultrasound Images Using Nonseparable Quincunx Wavelet Transform

被引：0

作者：

Shah, S. R. ^{[1
]}

Desai, M. D. ^{[2
]}

Panchal, L. ^{[3
]}

Desai, M. R. ^{[3
]}

机构：

[1] Dharmsinh Desai Univ, Coll Rd, Nadiad, Gujarat, India

[2] Kalo Inst Technol, Ahmadabad, Gujarat, India

[3] Kidney Hosp, Nadiad, Gujarat, India

来源：

5TH KUALA LUMPUR INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING 2011 (BIOMED 2011) | 2011年 / 35卷

关键词：

Classification; Texture characterization; Quincunx wavelet; Wavelet Decomposition; RECONSTRUCTION FILTER BANKS; DIFFUSE LIVER-DISEASE; TISSUE CHARACTERIZATION; CLASSIFICATION;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This paper describes an approach for texture characterization based on nonseparable quincunx wavelet decomposition transforms and its application for the discrimination of visually similar ultrasound renal stone images. The proposed feature extraction method applies quincunx wavelet transform and calculation of second order (GLCM) and FFT parameter form LL and HH part of decomposed image. This Characterization is experimented on a set of one hundred and twelve (112) different stones, which also validated with FTIR analysis in standard laboratory. It shows that GLCM, FFT transform evaluation in combination with quincunx wavelet decomposition could be a reliable method for a texture characterization.

引用

页码：611 / +

页数：2

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