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

Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification.

IEEE access : practical innovations, open solutions·2026

Same author

Data-Driven Discovery of Quaternary Ammonium Interlayers for Efficient and Thermally Stable Perovskite Solar Cells.

Advanced materials (Deerfield Beach, Fla.)·2026

Same author

Unbiased microRNA-Disease Association Prediction Using ICD-11 Codes and Negative Sampling.

Pharmacology research & perspectives·2025

Same author

DeepBiome: A Phylogenetic Tree Informed Deep Neural Network for Microbiome Data Analysis.

Statistics in biosciences·2025

Same author

Demonstration of Interoperability Between MIDRC and N3C: A COVID-19 Severity Prediction Use Case.

Journal of imaging informatics in medicine·2025

Same author

Multimodal data curation via interoperability: use cases with the Medical Imaging and Data Resource Center.

Scientific data·2025

Same journal

Blue Noise Dithering for Reservoir-based Spatio-temporal Importance Resampling.

IEEE transactions on visualization and computer graphics·2026

Same journal

ROS-GS: Relightable Outdoor Scenes With Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026

Same journal

MesoSplats: Texture Synthesis with Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026

Same journal

GLLA: A Unified Force-Directed Graph Layout Framework Supporting Local Adjustments.

IEEE transactions on visualization and computer graphics·2026

Same journal

Multi-Perception Crowd: Learning to combine entity and implicit perception for diverse crowd simulation.

IEEE transactions on visualization and computer graphics·2026

Same journal

Hiding in Plain Sight: Camouflaging Real-world Objects.

IEEE transactions on visualization and computer graphics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 25, 2026

Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature

Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature

Published on: April 5, 2013

Uncluttered Single-Image Visualization of Vascular Structures Using GPU and Integer Programming.

Joong-Ho Won, Yongkweon Jeon, Jarrett K Rosenberg

IEEE Transactions on Visualization and Computer Graphics

|February 1, 2012

Summary

This summary is machine-generated.

This study introduces a new method for visualizing complex 3D branching structures, like blood vessels, in a clear 2D image. The uncluttered single-image visualization (USIV) technique improves understanding and communication by preventing overlaps.

More Related Videos

Image-guided, Laser-based Fabrication of Vascular-derived Microfluidic Networks

Image-guided, Laser-based Fabrication of Vascular-derived Microfluidic Networks

Published on: January 3, 2017

An In Vitro 3D Model and Computational Pipeline to Quantify the Vasculogenic Potential of iPSC-Derived Endothelial Progenitors

An In Vitro 3D Model and Computational Pipeline to Quantify the Vasculogenic Potential of iPSC-Derived Endothelial Progenitors

Published on: May 13, 2019

Related Experiment Videos

Last Updated: May 25, 2026

Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature

Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature

Published on: April 5, 2013

Image-guided, Laser-based Fabrication of Vascular-derived Microfluidic Networks

Image-guided, Laser-based Fabrication of Vascular-derived Microfluidic Networks

Published on: January 3, 2017

An In Vitro 3D Model and Computational Pipeline to Quantify the Vasculogenic Potential of iPSC-Derived Endothelial Progenitors

An In Vitro 3D Model and Computational Pipeline to Quantify the Vasculogenic Potential of iPSC-Derived Endothelial Progenitors

Published on: May 13, 2019

Area of Science:

Biomedical Imaging
Computational Biology
Computer Graphics

Background:

Direct projection of 3D branching structures onto 2D images causes overlaps, hindering comprehension.
Visualizing complex vascular networks, such as the abdominal aorta, presents significant challenges in medical imaging.
Existing visualization methods may lack clarity or efficiency for complex anatomical structures.

Purpose of the Study:

To develop a novel method for creating uncluttered single-image visualizations (USIV) of 3D branching structures.
To demonstrate the utility of USIV in visualizing the abdominal aorta and its branches from tomographic data.
To introduce a new optimization technique for USIV inspired by protein structure prediction.

Main Methods:

Developed a novel optimization technique for uncluttered single-image visualization (USIV).
Utilized an integer linear programming-based formulation adapted from protein structure prediction.
Employed general-purpose graphics processing unit (GPGPU) technology for parallel processing and speedup.
Tested the technique on 30 visualizations from five patient scans of the abdominal aortic vessel tree.

Main Results:

Achieved high-quality 2D visualizations of the abdominal aorta without branch overlaps.
The novel optimization technique demonstrated significant computational speedup using GPGPU.
Visualization quality was comparable to previous methods, with substantial gains in computation time.
Successfully visualized anatomical variants in the abdominal aortic vessel tree.

Conclusions:

The proposed USIV method effectively visualizes complex 3D branching structures in a single, clear 2D image.
The novel optimization technique offers a significant improvement in computational efficiency for 3D to 2D visualization.
This approach enhances understanding and communication of complex anatomical data, particularly in vascular imaging.
The connection to protein structure prediction provides a powerful new avenue for geometric optimization problems.