Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Flow Cytometry01:23

Flow Cytometry

12.2K
The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
In...
12.2K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Label-free refractive index mapping of human sperm cells.

Biomedical optics express·2025
Same author

Rare cell classification using label-free imaging flow cytometry <i>via</i> motion-sensitive-triggered interferometry.

Lab on a chip·2025
Same author

The Synergic Effect of Tubal Endometriosis and Women's Aging on Fallopian Tube Function: Insights from a 3D Mechanical Model.

Bioengineering (Basel, Switzerland)·2024
Same author

Detection of bladder cancer cells using quantitative interferometric label-free imaging flow cytometry.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2024
Same author

Analyzing Blood Cells of High-Risk Myelodysplastic Syndrome Patients Using Interferometric Phase Microscopy and Fluorescent Flow Cytometry.

Bioengineering (Basel, Switzerland)·2024
Same author

On-chip label-free cell classification based directly on off-axis holograms and spatial-frequency-invariant deep learning.

Scientific reports·2023

相关实验视频

Updated: May 31, 2025

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy ATOM
07:19

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy ATOM

Published on: June 28, 2017

10.3K

基于直接基于多个离轴全息投影的细胞分类的无标签成像流细胞计.

Dana Aharoni1, Matan Dudaie1, Itay Barnea1

  • 1Tel Aviv University, Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv, Israel.

Journal of biomedical optics
|January 24, 2025
PubMed
概括

这项研究引入了一种新的,无标签的成像流细胞计法,用于实时细胞分类. 该技术使用全息投影的深度学习,显著提高白细胞分析的吞吐量和准确性.

科学领域:

  • 生物光子学和成像技术
  • 细胞生物学 细胞生物学
  • 机器学习在医学中的应用

背景情况:

  • 图像流细胞计 (IFC) 可以进行详细的细胞分析,但通常需要染色和复杂的处理.
  • 离轴全息提供无标签成像,但传统方法涉及计算密集的预处理,限制吞吐量.
  • 实时细胞分类对于高通量生物测试和临床诊断至关重要.

研究的目的:

  • 开发一个自动细胞分类方案,用于无污染IFC.
  • 直接利用离轴全息投影进行分类,而无需预处理.
  • 为了提高分类准确度和白细胞的吞吐量.

主要方法:

  • 一个专门的离轴全息显微镜系统是为获取流动中的白细胞而建造的.
  • 深度学习模型直接应用于离轴全息投影 (全息空间).
  • 用多个视角的全息投影来捕获全面的细胞信息.

主要成果:

  • 拟议的方法使用十个全息投影,与单个投影相比,实现了7.69%的精度改进.
  • 直接全息投影分析的性能比需要定量阶段形状预处理的方法高出17.95%.
  • 该技术简化了计算过程,使细胞分类吞吐量大幅增加.
关键词:
深度学习是一种深度学习.数字全息图是数字全息图.图像流动细胞计量 图像流动细胞计量

更多相关视频

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
08:58

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

Published on: November 19, 2018

12.4K
Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research
05:22

Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research

Published on: June 21, 2024

315

相关实验视频

Last Updated: May 31, 2025

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy ATOM
07:19

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy ATOM

Published on: June 28, 2017

10.3K
Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
08:58

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

Published on: November 19, 2018

12.4K
Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research
05:22

Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research

Published on: June 21, 2024

315

结论:

  • 这种无标签的IFC方法促进了蜂数据集的高通量,高内容分析.
  • 该方法显示了在临床环境中实时细胞分类的巨大潜力.
  • 对全息投影的直接分析为传统的IFC方法提供了更有效和更有信息的替代方案.