X-Ray Lung Image Classification Using a Canny Edge Detector

Abstract

The medical imaging technique is used in order to obtain a tissue image of a specific part of the human body without any surgical intervention. The presence of differences in the clinical experiences of a section of doctors or doctors in general can lead to discrepancies in the analysis and understanding of medical images and thus affects the accuracy of the diagnosis for the patient’s condition. The use of a medical imaging system for reliable diagnosis through the use of the computer will lead to high accuracy in diagnosis. For this reason, the need to improve the special performance of systems that perform computer-aided diagnosis used in the medical imaging process has increased special performance of the computer-aided diagnostic systems used in the medical imaging process. The medical image classification technique has the ability to perform a preliminary analysis as well as an understanding of medical images and also can identify the affected parts of the human body, which leads to helping doctors in the process of optimal diagnosis. The process of classifying medical images needs to extract the features of the image so that the classification process is carried out with high accuracy, and one of these features is detecting the edges of the image using a Canny edge detector. This is what the author performed in the research, and the experimental results show the effectiveness and goodness of this method.