Key points are not available for this paper at this time.
This review paper presents a comprehensive analysis of recent advancements in super-resolution applications in endoscopic imaging. It synthesizes findings from multiple cutting-edge research papers, each contributing unique methodologies and results. The review highlights the progression from traditional techniques to deep learning models, and attention mechanisms. Emphasis is placed on the practical application of these advancements in enhancing the quality of images for minimally invasive surgery, ultimately contributing to improved surgical outcomes. This synthesis not only showcases the current state of the field but also identifies potential areas for future research and development.
Hayat et al. (Thu,) studied this question.