Tuberculosis detection analysis using texture features on CXRs images

Badarudin Hakim, Basari

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Tuberculosis (TB) is one of the most common diseases in developing countries such as Indonesia. TB disease oftenly attacks the human lungs due to its high oxygen pressure. The basic characteristics of TB-infected lungs are in the form of wounds, which change its texture and shape. The common detection method is by comparing the X-ray thoracic image with the tuberculin skin test (TST) and fast acid staining methods. This diagnosis method is often constrained by the availability of radiologists in the health facilities. To overcome such situation, a computer-aided diagnosis (CAD) tool is required to assist the doctor read the X-ray images easily. In this paper, a complementary detection method is proposed by using a chest X-ray (CXR) image to assist the diagnosis process. In current method, the image is segmented to reduce unnecessary parts prior to preprocessing step. We use a texture-based feature approach for detection purpose because most of the common examination methods for abnormality detection on CXRs is by analyzing the change of textural (content) CXR. In our texture approach, we use texture-based statistical properties on the histogram's intensity. Some features that are used in this approach including Mean, Standard Deviation, Smoothness, Entropy, Root Mean Square (RMS), Variance, Kurtosis, Skewness, and Inverse Difference Moment (IDM). As a result of simulation, it indicates that CXR images can be well segmented to localize the focus area, allowing to the features can be extracted from the CXR image for further detection process. The obtained accuracy is about 93.94% and 92.86%, respectively for Shenzhen-Chest X-ray dataset and Montgomery County-Chest X-ray dataset.

Original languageEnglish
Title of host publication3rd Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, and Medical Devices
Subtitle of host publicationProceedings of the International Symposium of Biomedical Engineering, ISBE 2018
EditorsPraswasti P.D.K. Wulan, Misri Gozan, Sotya Astutiningsih, Ghiska Ramahdita, Radon Dhelika, Prasetyanugraheni Kreshanti
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735418226
DOIs
Publication statusPublished - 9 Apr 2019
Event3rd International Symposium of Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, and Medical Devices, ISBE 2018 - Jakarta, Indonesia
Duration: 6 Aug 20188 Aug 2018

Publication series

NameAIP Conference Proceedings
Volume2092
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference3rd International Symposium of Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, and Medical Devices, ISBE 2018
CountryIndonesia
CityJakarta
Period6/08/188/08/18

Keywords

  • CXR
  • feature extraction
  • image segmentation
  • tuberculosis detection

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