Sovereign Critique Network (SCN) Based Super-Resolution for chest X-rays images

Abstract

A prevalent and serious illness that affects people all over the globe is tuberculosis. A successful diagnosis of tuberculosis is essential for better survival rates and a successful course of treatment. Different techniques for detecting tuberculosis have been developed recently as a result of advancements in medical technology. These techniques have greatly increased the reliability and precision of tuberculosis detection. Finding tuberculosis at an early state, in which it is most treatable, is still a challenge. In order to improve the resolution of X-ray chest images for the early detection of tuberculosis, study is currently being done in this area. The Sovereign Critique Network (SCN) model is suggested in this article as a means of generating super resolution images from low-resolution X-ray images. The suggested SCN model is evaluated on the Tuberculosis (TB) Chest X-ray database for super resolution factors of 2, 4, and 6 separately with PSNR values of 31.85, 33.79, and 35.93 and SSIM values of 0.84, 0.91, and 0.96 for super resolution factors 2, 4, and 6, respectively. The proposed model shows promising results than any of the existing models.