Digital Edge Detection Based Pneumonia Detection in Chest Radiographs - Poola Rahul Gowtham; Kommineni Prema Teja; Lahari P.L; Yellampalli Siva Sankar (ITM Web of Conferences)
In response to the demand of pneumonia diagnosis, a digital detection algorithm utilizing chest X-ray images has been proposed. Despite this, X-ray images have the tendency of noise and spatial aliasing that tend to cause blurring of some boundaries, thus the importance of having a better edge detection algorithm is more warranted. The article presents a SIMULINK-based model for the process of edge detection, testing the performance of Canny, Laplacian of Gaussian, Prewitt, Sobel and Robert algorithms and most importantly their simulated results. Since some of the X rays are suspected to be afflicted by pneumonia, the radiographs are also converted into string numbers based on the features extracted as the Xray’s area of interest. One of the basic processes in image processing is the quality assessment of images, this work advocates for the inclusion of the objective criteria for the evaluation of the segmented images. Some performance evaluation metrics for various edge detection models are given and the relationships showed that the bacterial pneumonia affliction X rays have feature string values under 100 whereas the nonbacterial pneumonia X rays have values above 100.