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

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....

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Bibliographic Details
Published in:Computers in biology and medicine 2010-11, Vol.40 (11), p.931-942
Main Authors: Peng, Shao-Hu, Kim, Deok-Hwan, Lee, Seok-Lyong, Lim, Myung-Kwan
Format: Article
Language:English
Subjects:
Accuracy
CAD system
Classification
CT images
ELBP
Emphysema
Feature extraction
Female
Humans
Internal Medicine
Male
Methods
Other
Radiography, Thoracic - instrumentation
Radiography, Thoracic - methods
SGLDM
Studies
Texture features
Thorax
Tomography, X-Ray Computed - instrumentation
Tomography, X-Ray Computed - methods
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Summary: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 riu 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 riu 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).
ISSN:0010-4825
1879-0534
DOI:10.1016/j.compbiomed.2010.10.005