Jove
Visualize
联系我们

相关概念视频

Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

6.9K
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...
6.9K

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

Nanogap-Engineered Core-Shell-Like Nanostructures for Comprehensive SERS Analysis.

ACS applied materials & interfaces·2025
Same author

Enhanced Visible Light Controlled Glucose Photo-Reforming Using a Composite WO<sub>3</sub>/Ag/TiO<sub>2</sub> Photoanode: Effect of Incorporated Plasmonic Ag Nanoparticles.

Nanomaterials (Basel, Switzerland)·2024
Same author

Space-confined mediation of electron transfer for efficient biomolecular solar conversion.

Materials horizons·2024
Same author

New Concept for the Facile Fabrication of Core-Shell CuO@CuFe<sub>2</sub>O<sub>4</sub> Photocathodes for PEC Application.

Materials (Basel, Switzerland)·2022
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
查看所有相关文章
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

相关实验视频

Updated: Jun 3, 2025

Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

17.6K

空间稀疏物体的高分辨率单像素成像:近红外和可见波长范围的实时成像,增强了代处理或深度学习.

Rafał Stojek1,2, Anna Pastuszczak1, Piotr Wróbel1

  • 1Faculty of Physics, University of Warsaw, Pasteura 5, 02-093 Warsaw, Poland.

Sensors (Basel, Switzerland)
|January 8, 2025
PubMed
概括
此摘要是机器生成的。

高分辨率单像素成像 (SPI) 使用新型采样方案和优化重建实现了快速,动态的场景捕捉. 这使得与标准数字微镜设备 (DMD) 设置的各种应用程序的实时处理.

关键词:
压缩成像成像是一种压缩成像.计算成像技术的成像深度学习是一种深度学习.图像重建算法图像重建算法红外成像技术 红外成像技术信号处理 信号处理 信号处理一个像素的成像.

更多相关视频

Highly Resolved Intravital Striped-illumination Microscopy of Germinal Centers
10:07

Highly Resolved Intravital Striped-illumination Microscopy of Germinal Centers

Published on: April 9, 2014

10.0K
Author Spotlight: Comparative Imaging of Neural Activity in Awake and Freely Moving States
06:25

Author Spotlight: Comparative Imaging of Neural Activity in Awake and Freely Moving States

Published on: January 19, 2024

920

相关实验视频

Last Updated: Jun 3, 2025

Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

17.6K
Highly Resolved Intravital Striped-illumination Microscopy of Germinal Centers
10:07

Highly Resolved Intravital Striped-illumination Microscopy of Germinal Centers

Published on: April 9, 2014

10.0K
Author Spotlight: Comparative Imaging of Neural Activity in Awake and Freely Moving States
06:25

Author Spotlight: Comparative Imaging of Neural Activity in Awake and Freely Moving States

Published on: January 19, 2024

920

科学领域:

  • 光学和光子学 在光学和光子学.
  • 计算成像技术的成像
  • 机器学习应用 机器学习应用

背景情况:

  • 单像素成像 (SPI) 为传统相机提供了一种经济高效的替代方案,特别是在非可见波长方面.
  • 现有的SPI方法通常在分辨率,速度和重建复杂性方面面临限制.
  • 数字微镜设备 (DMD) 为SPI系统中的光学调制提供了一个多功能平台.

研究的目的:

  • 开发和验证动态场景的高分辨率单像素成像框架.
  • 优化采样方案和重建算法,以实现高效的数据采集和处理.
  • 评估代与基于神经网络的重建方法的性能.

主要方法:

  • 实现了一个新的SPI框架,使用数字微镜设备 (DMD) 以其原生1024x768分辨率.
  • 开发了一种两阶段的重建算法,包括通用反矩阵乘法和代和神经网络方法的比较分析.
  • 在可见和近红外波长中运行系统,压缩比为0.41%,测量速率为6.8Hz.

主要成果:

  • 在可见光谱和近红外光谱中实现了高分辨率SPI (1024x768).
  • 展示了与使用桌面GPU的图像采集速率相似的实时重建.
  • 神经网络重建在类似的训练数据中表现出色,而代方法提供了更广泛的适用性.

结论:

  • 拟议的SPI方法能够使用标准硬件和实时处理能力实现高分辨率,动态成像.
  • 优化的框架支持各种应用,需要快速获取和分析稀疏场景.
  • 该研究强调了SPI的代和神经网络重建之间的权衡.