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

The collection of speech data for the assessment of cognition remotely: Balancing ethical and practical challenges.

Alzheimer's & dementia (Amsterdam, Netherlands)·2026

Same author

Triple M Overlap Syndrome After Immune Checkpoint Inhibitors: A Case Series of a High-Mortality Phenotype.

JACC. Case reports·2026

Same author

Rapid coronary artery stent computational simulation using the simplex deformable model.

Medical engineering & physics·2026

Same author

Prediction of Post-stenting Lumen Dimensions Using High-Definition Intravascular Ultrasound.

JACC. Advances·2026

Same author

Postdilation Strategies Following Provisional Stenting of Left Main Coronary Bifurcations: Insights From Patient-Specific Computational Simulations.

JACC. Advances·2026

Same author

Redefining Physiology in the Cardiac Catheterization Laboratory.

The New England journal of medicine·2026

Same journal

Retraction.

The open biomedical engineering journal·2023

Same journal

Retraction Notice: Research and Implementation of Children's Speech Signal Processing System.

The open biomedical engineering journal·2019

Same journal

Retraction Notice: Research on Algorithm of Extracting PPG Signal for Detecting Atrial Fibrillation based on Probability Density Function.

The open biomedical engineering journal·2019

Same journal

Research and Implementation of Children's Speech Signal Processing System.

The open biomedical engineering journal·2019

Same journal

Research on Algorithm of Extracting PPG Signal for Detecting Atrial Fibrillation based on Probability Density Function.

The open biomedical engineering journal·2019

Same journal

F.E.M. Stress-Investigation of Scolios Apex.

The open biomedical engineering journal·2018

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 21, 2026

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery

Published on: December 6, 2024

Texture Analysis and Radial Basis Function Approximation for IVUS Image Segmentation.

Maria Papadogiorgaki¹, Vasileios Mezaris, Yiannis S Chatzizisis

¹Informatics and Telematics Institute, Centre for Research and Technology Hellas, 1st Km Thermi-Panorama Rd, P.O. Box 60361, GR-57001 Thermi-Thessaloniki, Greece.

The Open Biomedical Engineering Journal

|August 8, 2009

Summary

This summary is machine-generated.

A new automated method accurately detects lumen and media-adventitia borders in intravascular ultrasound (IVUS) images. This technique is crucial for 3D coronary artery reconstruction and assessing atherosclerotic lesions.

Keywords:

Intravascular ultrasound adventitia boundaries coronary arteries image segmentation lumen media texture analysis.

More Related Videos

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

Related Experiment Videos

Last Updated: Jun 21, 2026

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery

Published on: December 6, 2024

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

Area of Science:

Medical Imaging
Cardiovascular Research
Biomedical Engineering

Background:

Intravascular ultrasound (IVUS) is vital for clinical and research applications.
Accurate lumen and media-adventitia border detection in IVUS images is essential for 3D coronary artery reconstruction and atherosclerotic lesion assessment.

Purpose of the Study:

To develop a fully automated technique for detecting lumen and media-adventitia boundaries in IVUS images.
To improve the quantitative assessment of atherosclerotic lesions and facilitate 3D reconstruction.

Main Methods:

A two-step contour initialization process based on texture analysis.
Multilevel Discrete Wavelet Frames decomposition for texture analysis.
Radial Basis Function approximation for generating smooth, continuous contours.

Main Results:

The developed automated technique shows promising performance in detecting IVUS image boundaries.
The method offers an improvement over previous texture-based IVUS image analysis approaches.

Conclusions:

The automated IVUS border detection method is effective for clinical and research applications.
This technique supports accurate 3D reconstruction and quantitative assessment of coronary artery disease.