Texture feature extraction based on a uniformity estimation method for local brightness and structure in chest CT images

Authors:
Shao-Hu Peng;Deok-Hwan Kim;Seok-Lyong Lee;Myung-Kwan Lim
Affiliations:
Department of Electronic Engineering, Inha University, South Korea;Department of Electronic Engineering, Inha University, South Korea;School of Industrial and Management Engineering, Hankuk University of Foreign Studies, South Korea;Department of Radiology, Inha University Hospital, South Korea
Venue:
Computers in Biology and Medicine
Year:
2010

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Abstract

Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP^r^i^u^4) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP^r^i^u^4 and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM).