Threshold and Segmentation-Based X-ray Imaging Analysis for Covid-19 Detection

ABSTRACT

Diagnosing the novel Covid-19 disease is the best way to precluding the loss of human deaths. This research mainly concentrates on visually observable symptoms that can be seen on the lung X-rays of humans. Novel Covid-19 monitoring of health and diagnosing the disease in humans is very critical for sustainability to medical. Nowadays, it is difficult to detect the Covid-19 positive cases because of limited equipments, and also it needs the presence of medical experts in the identification of disease. Moreover, excessive processing time is required. For diagnosing the disease machine learning approaches play a very important role in the normal or abnormal state of Covid-19. For detection various steps are involved, such as acquisition of images, preprocessing, and segmentation of images. For automatic detection of Covid-19 disease, X-ray of lungs plays an important role. Hence we first segment it using various segmentation techniques in artificial intelligence. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.