A discrimination method for the detection of pneumonia using chest radiograph
Document Type
Article
Publication Date
1-1-2010
Abstract
This paper presents a statistical method for the detection of lobar pneumonia when using digitized chest X-ray films. Each region of interest was represented by a vector of wavelet texture measures which is then multiplied by the orthogonal matrix Q(2). The first two elements of the transformed vectors were shown to have a bivariate normal distribution. Misclassification probabilities were estimated using probability ellipsoids and discriminant functions. The result of this study recommends the detection of pneumonia by constructing probability ellipsoids or discriminant function using maximum energy and maximum column sum energy texture measures where misclassification probabilities were less than 0.15. (C) 2009 Elsevier Ltd. All rights reserved.
Keywords
Detection, Texture measures, Pneumonia, Principal component analysis (PCA), Discriminant analysis, Digital chest X-ray
Publication Title
Computerized Medical Imaging and Graphics
Volume
34
Issue
2
Publisher
Elsevier
Publisher Location
THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND