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基于图像配准和自适应窗口方向衬比的眼底散斑流成像

王佳 李一鸣 武文昌 周传清 杨晖

激光生物学报2025,Vol.34Issue(6):541-550,576,11.
激光生物学报2025,Vol.34Issue(6):541-550,576,11.DOI:10.3969/j.issn.1007-7146.2025.06.008

基于图像配准和自适应窗口方向衬比的眼底散斑流成像

Fundus Speckle Flow Imaging Based on Image Registration and Adaptive Window Directional Contrast

王佳 1李一鸣 2武文昌 2周传清 2杨晖1

作者信息

  • 1. 上海理工大学光电信息与计算机工程学院,上海 200093||上海健康医学院 数智眼健康诊疗技术与装备创新中心,上海 201318||上海健康医学院 医疗器械学院,上海 201318
  • 2. 上海健康医学院 数智眼健康诊疗技术与装备创新中心,上海 201318||上海健康医学院 医疗器械学院,上海 201318
  • 折叠

摘要

Abstract

In the monitoring,diagnosis,and clinical management of fundus diseases,the visualization of fundus vascular structures is recognized as of paramount importance for accurate pathological assessment.Laser speckle contrast imaging,a well-established non-invasive optical imaging technique,is capable of achieving vessel visualization and real-time dynamic blood flow monitoring,as contrast agents are not required.However,significant noise is inevitably introduced by the conventional contrast calculation method that employs a fixed-size sliding window.In the present study,laser speckle contrast images are aligned and fused with vascular structural images acquired via LED light illumination.Subsequent to fusion,the composite images are segmented into regional subsets,and region-specific optimal pixels are selected based on the variance criterion to perform contrast computation.Within the vascular boundary region,the geometry and dimensions of the analysis window are dynamically adjusted to adapt to the local vascular morphology.The results indicate that the contrast has been enhanced by 67.61%.Moreover,in deeper vascular imaging,the proposed method is found to yield superior noise reduction performance and enhanced image quality,thereby providing support for the diagnosis and management of ocular diseases.

关键词

激光散斑衬比成像/眼底/血流/图像配准/自适应窗口

Key words

laser speckle contrast imaging/fundus/blood flow/image registration/adaptive window

分类

医药卫生

引用本文复制引用

王佳,李一鸣,武文昌,周传清,杨晖..基于图像配准和自适应窗口方向衬比的眼底散斑流成像[J].激光生物学报,2025,34(6):541-550,576,11.

基金项目

上海市教育委员会人工智能项目(SHJWAIJK241201) (SHJWAIJK241201)

国家自然科学基金项目(12372384). (12372384)

激光生物学报

1007-7146

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