An Analysis of Chest X-ray by Laplacian Gaussian Filtering and Linear Opacity Judgment
Jin-Woo Kim · Journal of information and communication convergence engineering · 2008
We investigated algorithm to detect and characterize interstitial lung abnormalities seen at chest radiographs. This method includes a process of 4 directional Laplaction-Gaussian filtering, and a process of linear opacity judgment. Two regions of interest (ROIs) were selected in each right lung of patients, and these ROIs were processed by our computer-analyzing system. For quantitative analysis of interstitial opacities, the index, which is the percentage of opacity areas in a ROI, was obtained and evaluated in the images. From or result, abnormal lungs were well differentiated from normal lungs. In our algorithm, the processing results were not only given as the numeric data named radiographic index but also confirmed with radiologists observation on CRT. The approach, by which the interstitial abnormalities themselves are extracted, is good enough because the results can be confirmed by the observations of radiologists. In conclusion, our system is useful for the detection and characterization of interstitial lung abnormalities.