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相关概念视频

Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

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Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...
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Overview of Electron Microscopy01:25

Overview of Electron Microscopy

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The wavelengths of visible light ultimately limit the maximum theoretical resolution of images created by light microscopes. Most light microscopes can only magnify 1000X, and a few can magnify up to 1500X. Electrons, like electromagnetic radiation, can behave like waves, but with wavelengths of 0.005 nm, they produce significantly greater resolution up to 0.05 nm as compared to 500 nm for visible light. An electron microscope (EM) can create a sharp image that is magnified up to 2,000,000X.
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Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

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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.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
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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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Overview of Microscopy Techniques01:22

Overview of Microscopy Techniques

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The early pioneers of microscopy opened a window into the invisible world of microorganisms. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes that leveraged nonvisible light, such as fluorescence microscopy that uses an ultraviolet light source and electron microscopy that uses short-wavelength electron beams. These advances significantly improved magnification, image resolution, and contrast. By comparison, the...
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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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深度EM操场:将深度学习带到电子显微镜实验室

Hannah Kniesel1, Poonam Poonam1, Tristan Payer1

  • 1Visual Computing Group, Ulm University, Ulm, Germany.

Journal of microscopy
|June 28, 2025
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概括

深度EM游戏场使得电子显微镜 (EM) 实验室可以使用深度学习 (DL). 这个平台使EM研究人员能够培训和应用DL模型,弥合AI研究和实践实验室使用之间的差距.

关键词:
计算机视觉 计算机视觉深度学习是一种深度学习.电子显微镜的电子显微镜

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科学领域:

  • 电子显微镜电子显微镜
  • 人工智能的人工智能
  • 图像分析 图像分析

背景情况:

  • 深度学习 (DL) 已经彻底改变了图像分析,但其在电子显微镜 (EM) 实验室的采用受到可访问性和专业知识障碍的阻碍.
  • 电子商务专家往往缺乏实施和解释AI模型所需的编码技能和深度学习知识.
  • 在先进的DL研究与其在常规EM工作流程中的实际应用之间存在差距.

研究的目的:

  • 介绍DeepEM Playground,这是一个旨在民主化电子显微镜深度学习的交互平台.
  • 授权EM研究人员,无论他们的编码背景如何,培训,调整和应用DL模型.
  • 促进EM实验室内更深入地理解和整合人工智能驱动的图像分析.

主要方法:

  • 开发一个交互式,用户友好的平台,DeepEM游乐场.
  • 为DL模型培训和EM应用提供指导,实践的方法.
  • 专注于在EM专家中降低DL采用的入门障碍.

主要成果:

  • 深度EM游戏场使EM研究人员能够在没有广泛的编码专业知识的情况下参与DL方法.
  • 该平台支持DL模型的初始探索和高级定制,用于EM图像分析.
  • 促进了人工智能在EM工作流程中更有信心和更有效的整合.

结论:

  • 深度EM游乐场成功地弥合了DL研究和EM实验室实践之间的差距.
  • 该平台促进了对电子显微镜中人工智能驱动的分析的更大理解和采用.
  • 授权EM社区利用先进的DL工具进行增强的图像分析和发现.