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相关概念视频

Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

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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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Confocal Fluorescence Microscopy01:16

Confocal Fluorescence Microscopy

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Confocal microscopy is an advanced microscopic technique. The prime advantage of the confocal microscope over other microscopy techniques is its ability to block the out-of-focus light from the illuminated samples using pinholes. It is widely used with fluorescence optics to obtain high-resolution, sharp contrast images. Unlike optical microscopes, confocal microscopes use a focused beam of light laser to scan the entire sample surface at different z-planes. These microscopes are, therefore,...
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Three-Dimensional Microscopy in Microbiology01:28

Three-Dimensional Microscopy in Microbiology

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Three-dimensional imaging techniques are essential in cell biology, allowing researchers to visualize intricate cellular structures with high resolution. Two prominent methods, Differential Interference Contrast Microscopy (DIC) and Confocal Scanning Laser Microscopy (CSLM), provide distinct advantages for imaging live and thick specimens, respectively.Differential Interference Contrast MicroscopyDIC microscopy enhances contrast in transparent, unstained samples by converting phase...
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相关实验视频

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A Rapid Method for Multispectral Fluorescence Imaging of Frozen Tissue Sections
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A Rapid Method for Multispectral Fluorescence Imaging of Frozen Tissue Sections

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通过深度学习策略改善分散组织中的平面光显微镜.

Mohamad Feshki, Sylvain Martel, Yves De Koninck

    Optics express
    |July 21, 2023
    PubMed
    概括

    平面光显微镜 (FFM) 可以拍摄自由移动的动物,但光散射会降低图像质量. 深度学习模型与ADMM重建相结合,显著提高FFM图像质量在分散生物组织.

    科学领域:

    • 生物医学成像技术 生物医学成像技术
    • 光学工程是指光学工程.
    • 计算神经科学是一种神经科学.

    背景情况:

    • 肠道显微镜对于观察活体动物的生物过程至关重要.
    • 微型光显微镜可以进行神经电路观测,但受到庞大的光学技术的限制.
    • 平面光显微镜 (FFM) 为自由移动的动物成像提供了无镜头的替代方案,但在分散组织中面临着图像质量的挑战.

    研究的目的:

    • 为了提高平面光显微镜 (FFM) 的图像质量,用于在生物组织中进行体内成像.
    • 研究深度学习 (DL) 技术的应用,以通过散射介质增强FFM成像.
    • 开发和评估用于强大的FFM图像重建的计算模型.

    主要方法:

    • 开发一个整体的光线跟踪和蒙特卡罗FFM计算模型.
    • 评估深度学习模型通过散射介质进行成像.
    • 应用基于物理的DL模型与乘数交替方向方法 (ADMM) 结合用于图像重建.

    主要成果:

    • 使用ADMM的基于物理的DL模型在散射介质中展示了快速和强大的图像重建.
    • 与代模型相比,在分散介质上重建的FFM图像的结构相似度指数增加了多达20%.
    • 该研究介绍并讨论了在物理知情学习下FFM的DL方法相关的挑战.

    更多相关视频

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    Light Sheet-based Fluorescence Microscopy of Living or Fixed and Stained Tribolium castaneum Embryos
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    结论:

    • 深度学习显著提高FFM成像性能在分散生物组织.
    • 基于物理学的DL和ADMM的组合为高质量的体内显微镜提供了有前途的方法.
    • 需要对FFM的DL进行进一步的研究,包括监督和无监督学习.