A discrimination method for the detection of pneumonia using chest radiograph.
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.
Noor
Norliza Mohd
NM
Department of Electrical Engineering, Universiti Teknologi Malaysia, Jalan Semarak, Kuala Lumpur, Malaysia. norliza@ic.utm.my
Rijal
Omar Mohd
OM
Yunus
Ashari
A
Abu-Bakar
S A R
SA
D000465:Algorithms; D016002:Discriminant Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D011014:Pneumonia / Q000175:diagnosis*; D025341:Principal Component Analysis; D013902:Radiography, Thoracic