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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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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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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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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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相关实验视频

Updated: Sep 14, 2025

A Bright NIR-II Fluorescence Probe for Vascular and Tumor Imaging
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对于NIR-II光分子断层扫描的深度系统先前基于图形卷积网络.

Beilei Wang1, Shuangchen Li1, Heng Zhang1

  • 1School of Information Sciences and Technology, Northwest University, Xi'an, 710127, People's Republic of China; The Xi'an Key Laboratory of Radiomics and Intelligent Perception, Xi'an, People's Republic of China.

Computer methods and programs in biomedicine
|July 20, 2025
PubMed
概括

本研究介绍了用于光分子断层扫描 (FMT) 的深度系统先前基于图形卷积网络 (DSPGN). DSPGN在第二近红外窗 (NIR-II) 成像中提高了瘤位置精度和形状恢复.

关键词:
深度学习是一种深度学习.光分子断层扫描仪的光分子断层扫描仪.图形卷积网络中的图形卷积网络.第二个近红外窗口.

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相关实验视频

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科学领域:

  • 生物医学成像技术 生物医学成像技术
  • 医学物理 医学物理
  • 计算成像技术的成像

背景情况:

  • 光分子断层扫描 (FMT) 对早期瘤检测非常有价值.
  • 在FMT中严重的光子散射导致错误的反向问题,阻碍了准确性和形态重建.
  • 目前的FMT方法很难满足精确瘤成像的实际要求.

研究的目的:

  • 提高FMT的效率和准确性.
  • 为了提高FMT重建的形态性能.
  • 为了解决由光子散射引起的FMT的不良位置性质.

主要方法:

  • 使用第二次近红外 (NIR-II) 光成像来减少组织散射.
  • 开发了一个深度系统基于前置图形卷积网络 (DSPGN) 的FMT.
  • 将系统空间前置和图形结构纳入重建过程中.

主要成果:

  • 与现有方法相比,DSPGN在定位准确性方面表现优越.
  • 拟议的方法显著提高了FMT的形状恢复能力.
  • 数字模拟和体内实验都验证了DSPGN的有效性.

结论:

  • DSPGN有效地恢复光源的位置和形态.
  • 该方法显示了在NIR-II成像中推进FMT应用的潜力.
  • DSPGN为克服FMT固有的挑战提供了一个有希望的解决方案.