Macular pigment optical density and measurement technology based on artificial intelligence: a narrative review.

Journal: International journal of ophthalmology
Published Date:

Abstract

Macular pigment (MP) is a crucial pigment in the macular region. It plays an important role in filtering blue light, and exhibits anti-inflammatory and antioxidant properties. Macular pigment optical density (MPOD) is a key indicator for assessing the density of MP in the macular area and is closely associated with eye diseases, including age-related macular degeneration, diabetic retinopathy, and glaucoma. This review aims to explore the clinical significance of MPOD and its research value in ophthalmology and other medical fields. It summarizes the current MPOD measurement techniques, categorizing them into two main types ( and ), and discusses their respective advantages and limitations. Additionally, given the advancements in artificial intelligence (AI) and deep-learning technologies that offer new opportunities for improving MPOD assessment, this review analyzes the significant potential and future prospects of AI-based fundus image analysis in MPOD measurement. The goal of AI-based analysis is to provide faster and more accurate detection methods, thereby promoting further research and new clinical applications of MPOD in the field of ophthalmology.

Authors

  • Yu-Xuan Yuan
    School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, Gansu Province, China.
  • Hong-Yun Wu
    Ophthalmology Department, Ganzhou People's Hospital, Ganzhou 341000, Jiangxi Province, China.
  • Wen-Jin Yuan
    Department of Cardiology, Ganzhou People's Hospital, Ganzhou 341000, Jiangxi Province, China.
  • Yi-Lin Zhong
    Ophthalmology Department, Ganzhou People's Hospital, Ganzhou 341000, Jiangxi Province, China.
  • Zhe Xu
    Thayer School of Engineering at Dartmouth College Hanover NH USA john.zhang@dartmouth.edu.

Keywords

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