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通过MITM-Unet框架在多模光纤成像中进行高保真图像重建.

Zefeng Feng, Zengqi Yue, Wei Zhou

    Optics express
    |August 13, 2025
    PubMed
    概括

    一种新的成像方法使用多个斑点图案来改善从单一多模纤维的灰度图像重建. 这种多光斑照明类型的反向传输矩阵-Unet (MITM-Unet) 显著提高了紧型成像探测器的图像质量.

    科学领域:

    • 光学和光子学 在光学和光子学.
    • 生物医学成像技术 生物医学成像技术
    • 机器学习 机器学习

    背景情况:

    • 单一的多模纤维为超薄的成像探头提供了优势,但由于光斑照明不均而受到噪声的影响.
    • 复杂的灰度图像的高精度重建是传统方法的挑战.

    研究的目的:

    • 为单一多模光纤成像开发一个优化的图像重建框架.
    • 为了解决来自不均光斑照明的噪音问题,并改善灰度图像重建.

    主要方法:

    • 结合反向传输矩阵方法与深度神经网络 (Unet).
    • 集成多个照明条件和增加目标暴露以减轻噪音.
    • 开发了多光照明类型的反向传输矩阵-联网 (MITM-Unet) 方法.

    主要成果:

    • MITM-Unet显著优于单光照明类型 (SITM-Unet) 的性能.
    • MITM-Unet实现了结构相似度指数为0.59和皮尔森相关系数为0.91.
    • SITM-Unet实现了0.38的结构相似性指数和0.77.7的皮尔森相关系数.

    结论:

    • MITM-Unet 方法有效地从单一多模光纤系统中重建高质量的灰度图像.

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  • 这种方法为推进紧宽场内微镜成像提供了宝贵的见解.
  • 这项研究证明了使用多模纤维改善成像能力的潜力.