Application of phase congruency for discriminating some lung diseases using chest radiograph.
A novel procedure using phase congruency is proposed for discriminating some lung disease using chest radiograph. Phase congruency provides information about transitions between adjacent pixels. Abrupt changes of phase congruency values between pixels may suggest a possible boundary or another feature that may be used for discrimination. This property of phase congruency may have potential for deciding between disease present and disease absent where the regions of infection on the images have no obvious shape, size, or configuration. Five texture measures calculated from phase congruency and Gabor were shown to be normally distributed. This gave good indicators of discrimination errors in the form of the probability of Type I Error (δ) and the probability of Type II Error (β). However, since 1 -  δ is the true positive fraction (TPF) and β is the false positive fraction (FPF), an ROC analysis was used to decide on the choice of texture measures. Given that features are normally distributed, for the discrimination between disease present and disease absent, energy, contrast, and homogeneity from phase congruency gave better results compared to those using Gabor. Similarly, for the more difficult problem of discriminating lobar pneumonia and lung cancer, entropy and homogeneity from phase congruency gave better results relative to Gabor.
Institute of Mathematical Science, University of Malaya, Lembah Pantai, 50603 Kuala Lumpur, Malaysia.
Omar Mohd
OM
Rijal
Institute of Mathematical Science, University of Malaya, Lembah Pantai, 50603 Kuala Lumpur, Malaysia.
Hossein
H
Ebrahimian
UTM Razak School of Engineering and Advanced Technology, Universiti Teknologi Malaysia, UTM Kuala Lumpur Campus, Jalan Semarak, 54100 Kuala Lumpur, Malaysia.
Norliza Mohd
NM
Noor
Institute of Mathematical Science, University of Malaya, Lembah Pantai, 50603 Kuala Lumpur, Malaysia.
Amran
0000-0003-1320-0231
A
Hussin
Institute of Respiratory Medicine, Kuala Lumpur Hospital, Jalan Pahang, 50590 Kuala Lumpur, Malaysia.
Ashari
A
Yunus
Institute of Respiratory Medicine, Kuala Lumpur Hospital, Jalan Pahang, 50590 Kuala Lumpur, Malaysia.
Aziah Ahmad
AA
Mahayiddin
D000465:Algorithms; D006801:Humans; D008171:Lung Diseases / Q000000981:diagnostic imaging*; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D015233:Models, Statistical; D011014:Pneumonia / Q000000981:diagnostic imaging*; D011336:Probability; D015272:Pulmonary Medicine / Q000379:methods; D012372:ROC Curve; D013902:Radiography, Thoracic; D015203:Reproducibility of Results