Quantitative approaches in multimodal fundus imaging: State of the art and future perspectives.

计算机科学 背景(考古学) 定量评估 可靠性(半导体) 数据科学 医学影像学 人工智能 风险分析(工程) 医学 地理 量子力学 物理 功率(物理) 考古
作者
Alessandro Arrigo,Emanuela Aragona,Maurizio Battaglia Parodi,Francesco Bandello
出处
期刊:Progress in Retinal and Eye Research [Elsevier]
卷期号:92: 101111-101111 被引量:7
标识
DOI:10.1016/j.preteyeres.2022.101111
摘要

When it first appeared, multimodal fundus imaging revolutionized the diagnostic workup and provided extremely useful new insights into the pathogenesis of fundus diseases. The recent addition of quantitative approaches has further expanded the amount of information that can be obtained. In spite of the growing interest in advanced quantitative metrics, the scientific community has not reached a stable consensus on repeatable, standardized quantitative techniques to process and analyze the images. Furthermore, imaging artifacts may considerably affect the processing and interpretation of quantitative data, potentially affecting their reliability. The aim of this survey is to provide a comprehensive summary of the main multimodal imaging techniques, covering their limitations as well as their strengths. We also offer a thorough analysis of current quantitative imaging metrics, looking into their technical features, limitations, and interpretation. In addition, we describe the main imaging artifacts and their potential impact on imaging quality and reliability. The prospect of increasing reliance on artificial intelligence-based analyses suggests there is a need to develop more sophisticated quantitative metrics and to improve imaging technologies, incorporating clear, standardized, post-processing procedures. These measures are becoming urgent if these analyses are to cross the threshold from a research context to real-life clinical practice.
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