Classification of Infection and Fluid Regions in Chest X-Ray Images

Wan Siti Halimatul Munirah Wan Ahmad, Wan Mimi Diyana Wan Zaki, Mohammad Faizal Ahmad Fauzi, Wooi Haw Tan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper presents a study on the classification of consolidations in chest radiographs, namely the infection and fluid regions, using a block-based approach with Naïve Bayes classifier. The experiment is performed on infection and fluid regions within the lung, which are divided into 32-by-32 sub-blocks. Several feature extraction techniques are used to capture the block's low level features, and Naïve Bayes classifier is used to categorize each block to either normal, with infection or with fluid. At the region level, the regions are classified into the three categories based on the majority class of the blocks within the region. The performance of the system is evaluated based on its ability to classify the infection and fluid regions into specific abnormalities (infection or fluid or normal) as well as into general abnormality (abnormal or normal). Experimental results show very promising results, with Gabor transform recording the highest overall accuracy.

Original languageEnglish
Title of host publication2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509028962
DOIs
Publication statusPublished - 22 Dec 2016
Event2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016 - Gold Coast, Australia
Duration: 30 Nov 20162 Dec 2016

Other

Other2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016
CountryAustralia
CityGold Coast
Period30/11/162/12/16

Fingerprint

X rays
Fluids
Classifiers
Consolidation
Feature extraction
Experiments

Keywords

  • Chest abnormality
  • lung consolidation
  • medical image classification
  • Naive Bayes

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications

Cite this

Wan Ahmad, W. S. H. M., Wan Zaki, W. M. D., Ahmad Fauzi, M. F., & Tan, W. H. (2016). Classification of Infection and Fluid Regions in Chest X-Ray Images. In 2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016 [7797020] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DICTA.2016.7797020

Classification of Infection and Fluid Regions in Chest X-Ray Images. / Wan Ahmad, Wan Siti Halimatul Munirah; Wan Zaki, Wan Mimi Diyana; Ahmad Fauzi, Mohammad Faizal; Tan, Wooi Haw.

2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7797020.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wan Ahmad, WSHM, Wan Zaki, WMD, Ahmad Fauzi, MF & Tan, WH 2016, Classification of Infection and Fluid Regions in Chest X-Ray Images. in 2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016., 7797020, Institute of Electrical and Electronics Engineers Inc., 2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016, Gold Coast, Australia, 30/11/16. https://doi.org/10.1109/DICTA.2016.7797020
Wan Ahmad WSHM, Wan Zaki WMD, Ahmad Fauzi MF, Tan WH. Classification of Infection and Fluid Regions in Chest X-Ray Images. In 2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7797020 https://doi.org/10.1109/DICTA.2016.7797020
Wan Ahmad, Wan Siti Halimatul Munirah ; Wan Zaki, Wan Mimi Diyana ; Ahmad Fauzi, Mohammad Faizal ; Tan, Wooi Haw. / Classification of Infection and Fluid Regions in Chest X-Ray Images. 2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016. Institute of Electrical and Electronics Engineers Inc., 2016.
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