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Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
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对刺激拉曼光声显微镜信号分解技术的比较研究.

Amir Khansari1, Hossein Khodavirdi2,3, Seyed Mohsen Ranjbaran1

  • 1The Richard and Loan Hill Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, Illinois, USA.

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概括

快速里埃转换 (FFT) 方法在多光谱光声显微镜 (MS-PAM) 中的分解信号方面表现出色,用于准确估计氧和度. 其他方法在本研究中显示出更可变的性能.

关键词:
交叉相关性 交叉相关性深度学习是一种深度学习.多光谱光声显微镜学摄影声学 摄影声学信号的分解信号的分解

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科学领域:

  • 生物医学光学 生物医学光学
  • 摄影声学成像技术的成像
  • 频谱学是一种光谱学.

背景情况:

  • 多光谱光声学显微镜 (MS-PAM) 提供了功能性成像能力.
  • 刺激拉曼光谱 (SRS) 可以与MS-PAM集成,以提高分子对比度.
  • 准确的信号分解对于定量MS-PAM分析至关重要,特别是在估计氧和时.

研究的目的:

  • 在使用SRS的MS-PAM系统中比较评估不同信号分解技术的性能.
  • 为了评估快速里埃转换 (FFT),最小方程 (LSQ),交叉相关性 (XCorr) 和深度学习 (DL) 方法的准确性.
  • 确定MS-PAM中氧和估计的最佳方法.

主要方法:

  • 开发了MS-PAM系统,采用SRS与双波长激发 (532nm和558nm).
  • 实施并测试了四种信号分解算法:FFT,LSQ,XCorr和DL方法 (CNN自动编码器).
  • 经过验证的方法与地面真相相对照,来自小鼠大脑组织的光声学信号.

主要成果:

  • 与LSQ,XCorr和DL相比,FFT方法在信号分解方面表现出更高的准确性和一致性.
  • LSQ,XCorr和DL方法表现出性能变化,特别是在较长的时间延迟时.
  • 使用FFT分解信号估计氧和,可靠的结果.

结论:

  • FFT是基于SRS的MS-PAM中信号分解的最准确和最可靠的方法.
  • 这些发现支持使用FT用于定量功能成像,包括氧和映射.
  • 对于特定的MS-PAM应用程序,可能需要对LSQ,XCorr和DL方法进行进一步优化.