Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Super-resolution Fluorescence Microscopy

Super-resolution Fluorescence Microscopy

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

The mechanism underlying the quality deterioration effects of buckwheat flour on normal noodles: insights from its component perspectives.

Food research international (Ottawa, Ont.)·2026

Same author

An interpretable radiomics-machine learning model for early risk stratification of invasive fungal infections in community-acquired pneumonia: a dual-center study.

Scientific reports·2026

Same author

Post-pandemic shocks and non-suicidal self-injury risk in working-age adults: differential pathways via psychological distress and social support.

BMC public health·2026

Same author

Comparative effectiveness of non-pharmacological interventions for social anxiety disorder in adults: a systematic review and meta-analysis.

Frontiers in psychology·2026

Same author

Comparative effects of non-pharmacological interventions on anxiety, depression and quality of life in individuals with substance use disorders: A systematic review and network meta-analysis.

Journal of affective disorders·2026

Same author

Dual induction of tissue-resident T and B cell immunity for broad influenza protection with a nanofiber-VLP vaccine.

Journal of nanobiotechnology·2026

Same journal

Advancing microalgae biomass cultivation for an integrated sustainable wastewater treatment and resource recovery.

iScience·2026

Same journal

Corrigendum to "Human adipose ECM alleviates radiation-induced skin fibrosis via endothelial cell-mediated M2 macrophage polarization" [iScience, Volume 26, Issue 9 (2023) 107660].

iScience·2026

Same journal

High-definition transcranial direct current stimulation enhances exercise-induced hypoalgesia in patients with chronic low back pain.

iScience·2026

Same journal

From pre-tumor to tumor: Decoding the endoscopic-pathologic spectrum of neoplastic lesions in autoimmune gastritis.

iScience·2026

Same journal

Corrigendum to "A cobalt-aluminium layered double hydroxide with a nickel core-shell structure nanocomposite for supercapacitor applications" [iScience, 28 (2025) 111672].

iScience·2026

Same journal

Repurposing primaquine diphosphate for imatinib-resistant chronic myeloid leukemia via targeting BCR-ABL and Wnt/β-catenin pathway.

iScience·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 13, 2026

A Bright NIR-II Fluorescence Probe for Vascular and Tumor Imaging

A Bright NIR-II Fluorescence Probe for Vascular and Tumor Imaging

Published on: March 17, 2023

Deep learning-enabled high-performance multiphoton fluorescence vascular imaging using clinically approved

Zhourui Xu¹, Haoran Luo¹, Ting Chen²

¹School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, Guangdong 518055, China.

|January 9, 2026

Summary

This summary is machine-generated.

Deep learning enhances multiphoton fluorescence imaging (MPFI) using standard probes. This method clarifies deep tissue imaging, making MPFI more practical for clinical use.

Keywords:

Biocomputational method Nanoparticles Optical imaging

More Related Videos

Intravital Microscopy of Tumor-associated Vasculature Using Advanced Dorsal Skinfold Window Chambers on Transgenic Fluorescent Mice

Intravital Microscopy of Tumor-associated Vasculature Using Advanced Dorsal Skinfold Window Chambers on Transgenic Fluorescent Mice

Published on: January 19, 2018

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

Related Experiment Videos

Last Updated: Jan 13, 2026

A Bright NIR-II Fluorescence Probe for Vascular and Tumor Imaging

A Bright NIR-II Fluorescence Probe for Vascular and Tumor Imaging

Published on: March 17, 2023

Intravital Microscopy of Tumor-associated Vasculature Using Advanced Dorsal Skinfold Window Chambers on Transgenic Fluorescent Mice

Intravital Microscopy of Tumor-associated Vasculature Using Advanced Dorsal Skinfold Window Chambers on Transgenic Fluorescent Mice

Published on: January 19, 2018

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

Area of Science:

Biomedical Imaging
Deep Learning
Nanotechnology

Background:

Multiphoton fluorescence imaging (MPFI) offers high resolution for deep tissue visualization.
Existing clinical fluorescent probes are unsuitable for MPFI, limiting its clinical translation.
Biosafety of custom MPFI probes remains a significant concern.

Purpose of the Study:

To develop a deep learning method for high-performance MPFI using clinically approved probes.
To overcome limitations of current fluorescent probes in MPFI.
To enhance the clinical applicability of MPFI.

Main Methods:

A deep learning model was trained on aggregation-induced emission luminogen nanoparticle-based MPFI images.
The model was applied to MPFI data acquired using commercial quantum dots and indocyanine green (ICG).
The method was evaluated on its ability to process previously unseen MPFI data, particularly cerebral microvasculature.

Main Results:

The deep learning method demonstrated high performance on unseen MPFI data.
Significant optimization was observed in MPFI images of cerebral microvasculature.
Blood vessels in the hippocampus were visualized with exceptional clarity and reduced noise.

Conclusions:

The developed deep learning strategy effectively enhances MPFI performance with standard probes.
This approach improves the practicality and clinical applicability of MPFI.
The method offers a valuable solution for advancing deep tissue imaging in clinical settings.