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相关概念视频

Super-resolution Fluorescence Microscopy01:37

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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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Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
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相关实验视频

Updated: Jul 15, 2025

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
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深度学习驱动的自适应光学用于单分子定位显微镜.

Peiyi Zhang1, Donghan Ma1,2, Xi Cheng3,4

  • 1Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA.

Nature methods
|September 28, 2023
PubMed
概括
此摘要是机器生成的。

深度学习纠正生物组织中的异常,以获得更清晰的单分子局部化显微镜 (SMLM) 成像. 这种新的自适应光学方法提高了厚组织样本的分辨率和真实性.

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科学领域:

  • 生物物理学的生物物理.
  • 显微镜的使用方法
  • 光学工程是指光学工程.

背景情况:

  • 生物组织散射光线,扭曲单分子定位显微镜 (SMLM) 图像并限制分辨率.
  • 传统的自适应光学方法在复杂的组织环境中与不一致的反应作斗争.

研究的目的:

  • 为SMLM开发基于深度学习的自适应光学系统,直接补偿组织诱导的偏差.
  • 为了提高SMLM在厚厚的生物样本中的分辨率和图像准确度.

主要方法:

  • 一个深度神经网络被训练,从单分子发射模式推断波面扭曲.
  • 该系统使用动态波器和可变形镜来实现实时偏差补偿.
  • 该方法在脑组织样本的3D SMLM上进行了测试.

主要成果:

  • 深度学习方法直接推断并补偿波面扭曲.
  • 该系统成功地估计和纠正了28个波面变形形状.
  • 在 >130μm厚的大脑组织中,在分辨率和真实性方面取得了显著的改进.

结论:

  • 深度学习驱动的自适应光学为SMLM中的偏差校正提供了强大的解决方案.
  • 这种方法克服了传统适应光学在生物组织中的局限性.
  • 能够使高分辨率的3D SMLM成像更深入到分散的生物样本中.