Computer-aided detection of interstitial lung diseases: A texture approach
Tomas Plankis
Vilnius University
Algimantas Juozapavicius
Vilnius University
Eglė Stašienė
Vilnius University
Vytautas Usonis
Vilnius University
Published 2017-05-10


automatic lung disease recognition
image segmentation

How to Cite

Plankis T., Juozapavicius A., Stašienė E. and Usonis V. (2017) “Computer-aided detection of interstitial lung diseases: A texture approach”, Nonlinear Analysis: Modelling and Control, 22(3), pp. 404-411. doi: 10.15388/NA.2017.3.8.


We have developed the flexible scheme for computer-aided detection (CAD) of interstitial lung diseases on chest radiographs. These schemes enable us to perform diagnostics in the broad circumstances of pneumonia and other interstitial lung diseases. It is applied in the case of children pneumonia when conditions are difficult to standardize. In the adults' case the schemes of CAD are more adaptive, as there are more characteristic interstitial lung tissue's changes to all kinds of pathological conditions. Even in the norm of drawing there are more visible and more highlighted features, leading to better results. The CAD scheme works as follows. For the first of all, we are using adopted algorithms of active contours to select the area of lungs, and then to divide this area into subareas - regions of interest (40 different ROI). Then ROIs were subjected to the 2-dimensional Daubechies wavelet transform, and only main transformation was used. For every transformation 12 texture measures were calculated. Principal component analysis (PCA) was used to extract 2 main components for each ROI, and these components were compared to predictive component region.

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