Building an AI-Based Eye Cell Localization System

Abstract

Currently, ophthalmic medicine faces increasing demands for improved diagnostic efficiency and accuracy. The application of artificial intelligence (AI) technology offers an innovative solution to these challenges. This study leverages AI and deep learning algorithms to achieve precise localization of eye cells. By performing multi-layer processing on medical images, the system accurately delineates the contours of eye cells, enabling physicians to quickly assess patients' ocular health conditions.By integrating this system into the medical workflow, the reliance on manual identification is significantly reduced, thereby enhancing diagnostic efficiency and minimizing the risk of human error. Furthermore, the precise image analysis results assist doctors in formulating treatment plans more efficiently, providing patients with more accurate and personalized therapeutic solutions. The application of this technology extends beyond optimizing the diagnostic process, opening new possibilities for the integration of AI with medical science. In the future, such intelligent systems could be widely adopted for various medical imaging analyses, driving advancements in smart healthcare. As research progresses, this technology is expected to bring substantial improvements to ophthalmology and the broader medical field, enhancing overall healthcare quality and ensuring more comprehensive patient care.