ABSTRACT
Worldwide, COVID-19 has had a substantial impact on patients and hospital systems. Early identification and diagnosis are essential for regulating the growth of COVID-19. The input CT screening images are initially segmented into various regions using the Fuzzy C-means (FCM) clustering technique. Next, region-based image quality enhancement employs a histogram equalization method. Furthermore, certain necessary data is represented in a new image using the Local Directional Number technique. Lastly, the input images are portioned with the help of a traditional convolutional neural network model. The proposed convolutional neural network based system was able to give an accuracy of 98.60%, and the results revealed that methods for detecting COVID-19 impact from CT scan images must be developed significantly before considering it as a medical choice. Moreover, many diverse datasets are essential to assess the processes in a real-world setting. © 2022 IEEE.