Implementing a System for Diagnosing Pulmonary Fibrosis using Hough Algorithm

Abstract

The main objective of this paper by using image processing algorithms, mainly Hough algorithm, to develop a system which is able to analyze, process and put in evidence all the necessary features of a CT image for diagnosing pulmonary fibrosis. To approach the presented topic, image processing algorithms, image filtering, together with the Matlab work environment were combined and the optimal solution was finally implemented. The main idea behind the method is to identify two types of lines of the CT image which gives to the specialist the correct diagnostic by interpreting the obtained results. As final results, the chosen solution incorporates some crucial steps which have to be done in order to obtain the desired processed image with all the important details visible. The final solution was tested on different CT images and the medical specialist used it for detecting this type of disease, the detection being very easily mistaken.