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

42
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...
42
Acute Coronary Syndrome III: Diagnostic Studies01:30

Acute Coronary Syndrome III: Diagnostic Studies

10
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...
10
Coronary Artery Disease I: Introduction01:30

Coronary Artery Disease I: Introduction

25
Coronary Artery Disease (CAD): An Overview with Scientific InsightsCoronary Artery Disease (CAD), often referred to as C-A-D, is a prevalent blood vessel disorder classified under the broader category of atherosclerosis. Atherosclerosis is a pathological process characterized by the hardening and narrowing of arteries due to the accumulation of atherosclerotic plaques. These plaques are composed of cholesterol, fatty substances, inflammatory cells, calcium, and fibrin, reducing blood flow to...
25

You might also read

Related Articles

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

Sort by
Same author

CDM-UNet: Content-Driven Enhanced Mamba Model for Medical Image Segmentation.

Interdisciplinary sciences, computational life sciences·2026
Same author

A Bimodal Graph Neural Network with Transfer Learning and Contrastive Learning for Protein-Protein Interaction Site Prediction.

Interdisciplinary sciences, computational life sciences·2026
Same author

Prediction of Epilepsy Seizure Based on Cepstrum Analysis and Deep Learning.

Interdisciplinary sciences, computational life sciences·2025
Same author

NPI-HetGNN: A Prediction Model of ncRNA-Protein Interactions Based on Heterogeneous Graph Neural Networks.

Interdisciplinary sciences, computational life sciences·2025
Same author

ECMHA-PP: A Breast Cancer Prognosis Prediction Model Based on Energy-Constrained Multi-Head Self-Attention.

Proteomics. Clinical applications·2024
Same author

MFCC-CNN: A patient-independent seizure prediction model.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology·2024

Related Experiment Video

Updated: Jul 24, 2025

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
13:07

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

4.0K

Stenosis Detection and Quantification of Coronary Artery Using Machine Learning and Deep Learning.

Xinhong Zhang1, Boyan Zhang1, Fan Zhang2

  • 1School of Software, Henan University, Kaifeng, China.

Angiology
|July 3, 2023
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) algorithms, including machine learning and deep learning, are advancing coronary stenosis detection and quantification using computed tomography angiography (CTA). Challenges remain due to the need for large, annotated datasets for these AI methods.

Keywords:
artificial intelligencedeep learningmachine learningstenosis detectionstenosis quantification

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

1.0K
Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery
06:18

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

Published on: December 6, 2024

607

Related Experiment Videos

Last Updated: Jul 24, 2025

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
13:07

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

4.0K
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

1.0K
Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery
06:18

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

Published on: December 6, 2024

607

Area of Science:

  • Cardiology
  • Radiology
  • Artificial Intelligence

Background:

  • Coronary artery disease is a leading cause of mortality worldwide.
  • Accurate detection and quantification of coronary stenosis are crucial for patient management.
  • Computed tomography angiography (CTA) is a key imaging modality for assessing coronary arteries.

Purpose of the Study:

  • To review the applications of artificial intelligence (AI) algorithms for detecting and quantifying coronary stenosis using CTA.
  • To summarize recent advancements and discuss future trends in AI-driven coronary stenosis analysis.
  • To provide a comparative overview of different AI methods for researchers.

Main Methods:

  • Review of current literature on AI applications in coronary stenosis detection and quantification.
  • Focus on machine learning and deep learning techniques.
  • Analysis of the steps involved: vessel central axis extraction, segmentation, stenosis detection, and quantification.

Main Results:

  • AI, particularly machine learning and deep learning, shows significant promise for automating coronary stenosis detection and quantification.
  • These AI techniques are increasingly utilized in medical image segmentation and stenosis detection.
  • The review highlights the progress and comparative advantages/disadvantages of various AI methods.

Conclusions:

  • AI algorithms are poised to enhance the automation of coronary artery stenosis detection and quantification.
  • A major challenge for current AI methods is the requirement for extensive, expertly annotated datasets.
  • Further research is needed to overcome data annotation limitations and optimize AI technologies in this field.