Covid-19 disease has been known as a spreaded epidemic across the whole world that affects millions of people, causing deaths and catastrophic effects. For this reason, Computer Aided Diagnosis System (CAD), consists to be a crucial step using deep learning algorithms. In this context, a CNN network has been proposed using two optimizers networks such as Adam and Adadelta. The whole system is implemented on GPU with the aim to speed up the implementation time process. Then to have a medical real application which automatically detect the covid-19 class from CT scans images. Segmentations results achieved in terms of training and validation accuracies are 99.54% 99.65% respectively, outperforming the state of the art. Moreover, the predicted segmented images shows excellent results in terms of Mean Square Error reaching to 0.009, which is close to zero, compared to the ground truth. As a result, a medical real time application is achieved for Covid-19 class segmentation in a short time process. © 2021 IEEE.
CT-Scans Images Segmentation for COVID-19 Detection Based CNN Models