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Updated: Jun 23, 2025

Inducement and Evaluation of a Murine Model of Experimental Myopia
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视网膜图像记录方法用于近视发展的近视.

Zengshuo Wang1, Haohan Zou2, Yin Guo3

  • 1Nankai University Eye Institute, Nankai University, Tianjin 300350, China; Institute of Robotics and Automatic Information System (IRAIS), the Tianjin Key Laboratory of Intelligent Robotic (tjKLIR), Nankai University, Tianjin 300350, China.

Medical image analysis
|June 20, 2024
PubMed
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此摘要是机器生成的。

准确的视网膜图像注册对于研究近视发展至关重要. 这种新的3D空间模型和注册框架提高了近视眼睛的准确性,有助于研究.

科学领域:

  • 眼科医生 眼科 眼科
  • 医疗成像医学成像
  • 计算机视觉 计算机视觉

背景情况:

  • 近视发展改变了视网膜结构和眼轴长度.
  • 准确地记录视网膜图像对于分析这些变化至关重要.
  • 现有的方法面临着视网膜曲和近视引起的扭曲的挑战.

研究的目的:

  • 在近视发展的背景下,提高视网膜图像的注册准确性.
  • 为应对近视眼中视网膜曲和眼轴延长所带来的挑战.

主要方法:

  • 一个新的3D空间模型,包含近视发展模拟 (眼轴长度,眼底曲).
  • 包含一个基底摄像头扭曲模型.
  • 一个使用对应点进行3D姿势估计的注册框架.

主要成果:

  • 关于公共和FIMD数据集的定量评估.
  • 与最先进的方法相比,证明了卓越的准确性和稳定性.
  • 影响近视发展的视网膜图像的有效注册.

结论:

  • 介绍了第一个视网膜图像注册方法,专门用于近视发展研究.
关键词:
摄像机的扭曲模型视网膜底部图像 视网膜底部图像近视发展近视发展近视发展模式 近视发展模式视网膜图像的注册 视网膜图像的注册

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  • 显著提高近视视网膜图像的注册准确性.
  • 介绍了公开可用的Fundus影像近视发展 (FIMD) 数据集.