COVID-19 Lung Infection Segmentation
Omar Elharrouss, Nandhini Subramanian, Noor Almaadeed, Somaya Al-Máadeed
Abstract
The novelty of the COVID-19 Disease and the speed of spread, that created a colossal chaos, and impulse in the worldwide researchers to exploit all resources and capabilities to understand and analyze characteristics of the Coronavirus in terms of spread and virus incubation time. For that, the existing medical features like CT and X-ray images are used. For example, CT-scan images can be used for the detection of lung infection. But the challenges of these features such as the quality of the image and infection characteristics limit the effectiveness of these features. Using artificial intelligence (AI) tools and computer vision algorithms, the accuracy of detection can be more accurate and can help to overcome these issues. This poster proposes a multi-task deeplearning-based method for lung infection segmentation using CT-scan image.