Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

50
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...
50
Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

224
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...
224
Radiological Investigation III: Pulmonary Angiogram and PET Scan01:13

Radiological Investigation III: Pulmonary Angiogram and PET Scan

131
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...
131
Acute Coronary Syndrome III: Diagnostic Studies01:30

Acute Coronary Syndrome III: Diagnostic Studies

15
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...
15
Imaging Studies for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

52
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...
52

You might also read

Related Articles

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

Sort by
Same author

Papilledema and related clinical and paraclinical visual assessment in cerebral venous and sinus thrombosis versus idiopathic intracranial hypertension.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology·2026
Same author

Response to letter to the editor.

Journal of cardiology·2026
Same author

Prognosis of acute myocarditis beyond hospitalization: Results of a long-term prospective study.

Revista portuguesa de cardiologia : orgao oficial da Sociedade Portuguesa de Cardiologia = Portuguese journal of cardiology : an official journal of the Portuguese Society of Cardiology·2026
Same author

Atrial Septal Defect Closure With Persistently Elevated Pulmonary Vascular Resistance.

JACC. Case reports·2026
Same author

Correction: Impact of Aspirin on Primary Prevention of Cardiovascular Events in Patients with Elevated Lipoprotein(a): A Systematic Review and Meta-analysis.

American journal of cardiovascular drugs : drugs, devices, and other interventions·2026
Same author

iCARDIO Alliance global implementation guidelines for the management of obesity 2025 focus on prevention and treatment of cardiometabolic disease.

American journal of preventive cardiology·2026

Related Experiment Video

Updated: Aug 3, 2025

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.8K

Coronary X-ray angiography segmentation using Artificial Intelligence: a multicentric validation study of a deep

Miguel Nobre Menezes1,2, João Lourenço Silva3, Beatriz Silva4,5

  • 1Structural and Coronary Heart Disease Unit, Faculdade de Medicina, Cardiovascular Center of the University of Lisbon, Universidade de Lisboa (CCUL@RISE), Av Prof. Egas Moniz, Lisboa, 1649-028, Portugal. mnmenezes.gm@gmail.com.

The International Journal of Cardiovascular Imaging
|April 7, 2023
PubMed
Summary

An artificial intelligence (AI) model accurately segmented coronary angiography (CAG) images across multiple centers. This deep learning approach shows promise for future clinical applications in cardiovascular imaging.

Keywords:
Artificial IntelligenceCoronary angiographyCoronary artery diseaseDeep learningMachine learningPercutaneous coronary intervention.

More Related Videos

Author Spotlight: Advancing Cardiovascular Imaging - Introducing the Spatially Weighted Calcium Score for Early Disease Detection
06:57

Author Spotlight: Advancing Cardiovascular Imaging - Introducing the Spatially Weighted Calcium Score for Early Disease Detection

Published on: September 22, 2023

1.1K
Deep Learning-Based Segmentation of Cryo-Electron Tomograms
10:25

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

9.0K

Related Experiment Videos

Last Updated: Aug 3, 2025

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.8K
Author Spotlight: Advancing Cardiovascular Imaging - Introducing the Spatially Weighted Calcium Score for Early Disease Detection
06:57

Author Spotlight: Advancing Cardiovascular Imaging - Introducing the Spatially Weighted Calcium Score for Early Disease Detection

Published on: September 22, 2023

1.1K
Deep Learning-Based Segmentation of Cryo-Electron Tomograms
10:25

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

9.0K

Area of Science:

  • Cardiovascular Imaging
  • Artificial Intelligence in Medicine
  • Medical Image Analysis

Background:

  • An artificial intelligence (AI) model for automatic coronary angiography (CAG) segmentation using deep learning was previously developed.
  • This study aimed to validate the AI model's performance on a new, independent dataset.

Purpose of the Study:

  • To assess the accuracy and reliability of a deep learning-based AI model for automatic CAG segmentation.
  • To validate the AI model's performance on a multicentric dataset, evaluating its clinical applicability.

Main Methods:

  • Retrospective analysis of 117 CAG images from 90 patients across four centers.
  • AI model segmentation was compared against validated Quantitative Coronary Analysis (QCA) software.
  • Key metrics included lesion diameter, area overlap, sensitivity, Dice Score, and Global Segmentation Score (GSS).

Main Results:

  • The AI model demonstrated high accuracy with 99.9% overlap accuracy, 95.1% sensitivity, and 94.8% Dice Score.
  • No significant differences were found in lesion diameter or percentage diameter stenosis between AI-segmented and original images.
  • The Global Segmentation Score (GSS) was 92, consistent with previous findings, indicating robust performance.

Conclusions:

  • The AI model achieved accurate CAG segmentation on a multicentric validation dataset, confirming its efficacy.
  • The model's performance across various metrics supports its potential for clinical use in cardiovascular imaging.
  • This validation paves the way for further research into the clinical applications of AI in coronary angiography.