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

Imaging Studies VII: Vascular Imaging

Imaging Studies VII: Vascular Imaging

DefinitionRenal angiography, also known as renal arteriography, is an imaging technique used to obtain a comprehensive view of blood flow and the vascular structure of blood vessels in the kidneys and surrounding areas.PurposeRenal angiography detects blood vessel abnormalities in the kidneys, such as aneurysms, stenosis, thrombosis, vascular tumors, and renal artery stenosis. It evaluates kidney function and guides interventional treatments like angioplasty or stent placement.Pre-Procedure...

You might also read

Related Articles

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

Sort by

Same author

Intraoperative tracking of tissue perfusion during cerebral aneurysm surgery with laser speckle contrast imaging: insights beyond standard intraoperative neuromonitoring for detecting ischemia.

Neurophotonics·2026

Same author

Fault-tolerant pedigree reconstruction from pairwise kinship relations.

Bioinformatics (Oxford, England)·2026

Same author

Mapping fast tissue dynamics with long camera exposures via intensity modulation.

Proceedings of the National Academy of Sciences of the United States of America·2026

Same author

Deep learning-based precision phenotyping of spine curvature identifies novel genetic risk loci for scoliosis in the UK Biobank.

NPJ digital medicine·2026

Same author

Multi-exposure speckle imaging through an optical fiber bundle.

Journal of biomedical optics·2025

Same author

Improving vascular retention of indocyanine green for <i>in vivo</i> two-photon microscopy using liposomal encapsulation.

Journal of biomedical optics·2025

Search research articles

Related Experiment Video

Updated: May 7, 2026

A Method for 2-Photon Imaging of Blood Flow in the Neocortex through a Cranial Window

A Method for 2-Photon Imaging of Blood Flow in the Neocortex through a Cranial Window

Published on: February 25, 2008

A Deep Learning Approach for Improving Two-Photon Vascular Imaging Speeds.

Annie Zhou¹, Samuel A Mihelic¹, Shaun A Engelmann¹

¹Department of Biomedical Engineering, The University of Texas at Austin, 107 W. Dean Keeton C0800, Austin, TX 78712, USA.

Bioengineering (Basel, Switzerland)

|February 23, 2024

Summary

We developed a fast AI algorithm to improve 3D imaging of brain blood vessels using multiphoton fluorescence microscopy (MPF). This method significantly speeds up image acquisition, enabling better tracking of neurovascular disease progression in preclinical models.

Keywords:

deep learning fast upscaling multiphoton imaging vascular segmentation and vectorization

More Related Videos

In Vivo Three-Dimensional Two-Photon Microscopy to Study Conducted Vascular Responses by Local ATP Ejection Using a Glass Micro-Pipette

In Vivo Three-Dimensional Two-Photon Microscopy to Study Conducted Vascular Responses by Local ATP Ejection Using a Glass Micro-Pipette

Published on: June 7, 2019

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: May 7, 2026

A Method for 2-Photon Imaging of Blood Flow in the Neocortex through a Cranial Window

A Method for 2-Photon Imaging of Blood Flow in the Neocortex through a Cranial Window

Published on: February 25, 2008

In Vivo Three-Dimensional Two-Photon Microscopy to Study Conducted Vascular Responses by Local ATP Ejection Using a Glass Micro-Pipette

In Vivo Three-Dimensional Two-Photon Microscopy to Study Conducted Vascular Responses by Local ATP Ejection Using a Glass Micro-Pipette

Published on: June 7, 2019

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:

Neuroscience
Biomedical Imaging
Computational Biology

Background:

Multiphoton fluorescence microscopy (MPF) enables high-resolution imaging of cerebral vasculature for tracking neurovascular disease.
Traditional MPF is time-consuming, limiting sample sizes for chronic studies.
Acquiring paired low- and high-resolution images for training AI models is challenging.

Purpose of the Study:

To develop a fast, AI-based method for upscaling low-resolution MPF images.
To enable efficient 3D reconstruction and analysis of vascular networks.
To demonstrate the utility of semi-synthetic data for training AI models in MPF.

Main Methods:

A convolutional neural network (PSSR Res-U-Net) was used for image upscaling.
A segmentation-less vectorization process was employed for 3D reconstruction.
Semi-synthetic training data was utilized to train the AI model.

Main Results:

The AI algorithm significantly reduces MPF imaging time by up to fourfold.
The method successfully reconstructs and analyzes 3D vascular networks from upscaled images.
The approach generalizes across different imaging depths and disease states in mouse models.
Using semi-synthetic data yields comparable results to using real image pairs.

Conclusions:

This AI-driven approach accelerates MPF imaging for neurovascular research.
The method facilitates more extensive preclinical studies of neurovascular diseases.
The use of semi-synthetic data offers a practical solution for training AI in challenging imaging scenarios.