在基于图像算法的激光光斑对比成像中增强血管可视化
Long Yan1, Gongzhi Du1, Xiaozheng Huang1
1Wuhan Institute of Technology, Hubei Key Laboratory of Optical Information and Pattern Recognition, Wuhan, China.
Journal of biomedical optics
|May 30, 2025
概括
先进的图像处理技术显著增强了激光光斑对比成像 (LSCI) 以获得更清晰的血液流动可视化. 这些方法解决了运动器件和噪音,改善了生物医学应用中的血管成像.
科学领域:
- 生物医学成像技术 生物医学成像技术
- 光学连贯性断层扫描技术
- 医疗图像处理 医学图像处理
背景情况:
- 激光斑点对比成像 (LSCI) 在实际生物医学应用中面临挑战,因为运动工件和噪音.
- 这些文物损害了LSCI血管可视化的清晰度和有效性.
研究的目的:
- 通过增强图像注册,无声化和多焦图像融合来改善LSCI中的血液流动可视化.
- 为了减轻运动器件和噪音,以获得更准确的血管成像.
主要方法:
- 使用卢卡斯-卡纳德 (LK) 光流金字塔方法进行图像注册.
- 采用区块匹配和3D过 (BM3D) 与指导过和总变异规范化用于消除噪音.
- 实施了基于多尺度图像对比放大 (MUSICA) 算法的多焦点图像融合技术.
主要成果:
- 与非注册方法相比,LK光流记录改善了信号噪声比和图像质量.
- 增强的BM3D方法在LSCI图像评估中表现优于经典的无色化算法.
- 与失焦图像相比,基于MUSICA的融合方法在图像质量评估中实现了近六倍的改进.
结论:
- 图像处理在注册,无声化和多焦融合方面的进步显著增强了LSCI.
- 这些改进导致了对血管血流的卓越可视化,用于实际的生物医学应用.
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