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 for Cardiovascular System III: X-Ray

Imaging Studies for Cardiovascular System III: X-Ray

The most common cardiovascular diagnostic test is an X-ray. It produces images of the heart, blood vessels, and adjacent structures.
Definition and Purpose
An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...

Acute Coronary Syndrome III: Diagnostic Studies

Acute Coronary Syndrome III: Diagnostic Studies

Diagnosing acute coronary syndrome or ACS begins with a thorough patient history. Notable symptoms include central, crushing chest pain radiating to the left arm, neck, jaw, or back, along with shortness of breath, sweating (diaphoresis), nausea, vomiting, dizziness, and palpitations.It is crucial to note any history of cardiac illnesses and assess risk factors, including age, gender, smoking, hypertension, diabetes, hyperlipidemia, and a sedentary lifestyle.During physical examination, vital...

Imaging Studies for Cardiovascular System V: CT

Imaging Studies for Cardiovascular System V: CT

Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...

X-ray Imaging

X-ray Imaging

German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with X-rays, and by 1900, X-ray was widely...

Radiological Investigation III: Pulmonary Angiogram and PET Scan

Radiological Investigation III: Pulmonary Angiogram and PET Scan

Radiological investigations are paramount in the diagnosis and management of various pulmonary diseases. Two essential investigations are the Pulmonary Angiogram and the Positron Emission Tomography (PET) Scan.
Pulmonary Angiogram
A Pulmonary Angiogram is an invasive procedure involving injecting a contrast medium through a catheter threaded into the pulmonary artery or the right side of the heart to visualize the pulmonary vasculature. Computed Tomography (CT) scans have mainly replaced this...

You might also read

Related Articles

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

Sort by

Same author

The Association of Aortic Stenosis Severity and Symptom Status With Morbidity and Mortality.

JACC. Advances·2025

Same author

Physician assessment of aortic stenosis severity, quantitative parameters, and long-term outcomes: Results from the KP-VALVE project.

American heart journal·2023

Same author

P2Y12 Inhibitors in Acute Coronary Syndromes: A Real-World, Community-Based Comparison of Ischemic and Bleeding Outcomes.

Journal of interventional cardiology·2023

Same author

Predicting short-term outcomes after transcatheter aortic valve replacement for aortic stenosis.

American heart journal·2022

Same author

Contemporary Trends, Predictors and Outcomes of Perforation During Percutaneous Coronary Intervention (From the NCDR Cath PCI Registry).

The American journal of cardiology·2020

Same author

Coronary Artery Bypass Grafting Versus Percutaneous Coronary Intervention for Unprotected Left Main Disease - A Review.

Interventional cardiology (London, England)·2018

Search research articles

Related Experiment Video

Updated: May 15, 2026

Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans

Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans

Published on: August 28, 2018

Finding similar 2D X-ray coronary angiograms.

Tanveer Syeda-Mahmood¹, Fei Wang, R Kumar

¹IBM Almaden Research Center, San Jose, CA, USA.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

|January 5, 2013

Summary

Physicians can now automatically find similar coronary angiograms using visual features. This method aids in assessing patient disease states by matching current angiograms with historical data.

More Related Videos

Two-Dimensional X-Ray Angiography to Examine Fine Vascular Structure Using a Silicone Rubber Injection Compound

Two-Dimensional X-Ray Angiography to Examine Fine Vascular Structure Using a Silicone Rubber Injection Compound

Published on: January 7, 2019

Semi-Automatic Graphical Tool for Measuring Coronary Artery Spatially Weighted Calcium Score from Gated Cardiac Computed Tomography Images

Semi-Automatic Graphical Tool for Measuring Coronary Artery Spatially Weighted Calcium Score from Gated Cardiac Computed Tomography Images

Published on: September 22, 2023

Related Experiment Videos

Last Updated: May 15, 2026

Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans

Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans

Published on: August 28, 2018

Two-Dimensional X-Ray Angiography to Examine Fine Vascular Structure Using a Silicone Rubber Injection Compound

Two-Dimensional X-Ray Angiography to Examine Fine Vascular Structure Using a Silicone Rubber Injection Compound

Published on: January 7, 2019

Semi-Automatic Graphical Tool for Measuring Coronary Artery Spatially Weighted Calcium Score from Gated Cardiac Computed Tomography Images

Semi-Automatic Graphical Tool for Measuring Coronary Artery Spatially Weighted Calcium Score from Gated Cardiac Computed Tomography Images

Published on: September 22, 2023

Area of Science:

Cardiovascular Imaging
Medical Image Analysis
Computational Pathology

Background:

Clinical assessment of coronary artery disease relies on physician expertise in interpreting coronary angiograms.
Visual features like arterial tortuosity and junction distance are key to manual assessment.
A need exists for automated methods to support clinical decision-making.

Purpose of the Study:

To develop an automated method for extracting visual features from coronary angiograms.
To utilize these features for efficiently searching large databases of coronary angiograms.
To identify angiograms from patients with similar clinical histories.

Main Methods:

Automated extraction of visually relevant features from coronary artery images.
Development of a system for querying coronary angiogram databases based on extracted features.
Utilizing features such as distance from the root and arterial tortuosity.

Main Results:

Successful automatic extraction of key visual features from coronary angiograms.
Demonstrated ability to find clinically similar coronary angiograms within a large database.
Validation on a large dataset confirmed the method's effectiveness in matching patients with similar clinical histories.

Conclusions:

Automated feature extraction from coronary angiograms can replicate and enhance clinical similarity assessment.
This technology offers a powerful tool for managing and analyzing large collections of cardiovascular imaging data.
The method has the potential to improve diagnostic efficiency and patient care in cardiology.