系统梳理眼底图像质量评估与增强技术，助力基层眼科诊疗
Fundus Image Quality Assessment and Enhancement: a Systematic Review
- 梳理眼底成像干扰因素与质量评估增强方法
- 总结现有算法与临床部署中的关键挑战
- 适合眼科AI研究者与医疗影像工程师参考
眼底摄影作为一种低成本、便捷的眼部扫描方式，具有预防视力损伤的潜力，尤其在资源有限地区。然而，在复杂成像环境下，眼底图像退化普遍，影响后续诊断与治疗。因此，图像质量评估（IQA）与增强（IQE）对保障眼底图像的临床价值与可靠性至关重要。尽管已有综述涵盖该领域部分内容，但缺乏对IQA与IQE相互作用及临床落地挑战的系统分析。本文通过全面回顾眼底IQA与IQE算法、研究进展与实际应用，首先阐述眼底摄影成像系统基础及其干扰因素，随后系统总结IQA与IQE的主要范式。此外，讨论了实际部署中的挑战与解决方案，并提出未来研究方向的见解。
原文摘要 · Abstract (English)
As an affordable and convenient eye scan, fundus photography holds the potential for preventing vision impairment, especially in resource-limited regions. However, fundus image degradation is common under intricate imaging environments, impacting following diagnosis and treatment. Consequently, image quality assessment (IQA) and enhancement (IQE) are essential for ensuring the clinical value and reliability of fundus images. While existing reviews offer some overview of this field, a comprehensive analysis of the interplay between IQA and IQE, along with their clinical deployment challenges, is lacking. This paper addresses this gap by providing a thorough review of fundus IQA and IQE algorithms, research advancements, and practical applications. We outline the fundamentals of the fundus photography imaging system and the associated interferences, and then systematically summarize the paradigms in fundus IQA and IQE. Furthermore, we discuss the practical challenges and solutions in deploying IQA and IQE, as well as offer insights into potential future research directions.
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