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 V: CT01:28

Imaging Studies for Cardiovascular System V: CT

94
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...
94
Computed Tomography01:10

Computed Tomography

6.9K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
6.9K
Aortic Regurgitation II: Clinical Features and Diagnostic Tests01:22

Aortic Regurgitation II: Clinical Features and Diagnostic Tests

75
Aortic valve regurgitation (AR) occurs when the aortic valve fails to close properly, allowing blood to flow backward from the aorta into the left ventricle. This backflow can result in two distinct clinical presentations: acute and chronic AR, each characterized by its own set of symptoms and physical findings.Acute Aortic RegurgitationAcute AR presents with a sudden onset of severe symptoms. Patients typically experience profound dyspnea (shortness of breath), chest pain, and signs of left...
75
Aneurysm II: Clinical Manifestations and Diagnostic Studies01:21

Aneurysm II: Clinical Manifestations and Diagnostic Studies

46
Thoracic, aortic arch and abdominal aneurysms are significant vascular conditions that can present with various clinical manifestations and lead to serious complications. Understanding these manifestations and the appropriate diagnostic studies is essential for effective management and treatment.Thoracic Aortic AneurysmsThoracic aortic aneurysms often remain asymptomatic until they reach a size that impinges on adjacent structures. They typically cause deep, diffuse chest pain that radiates to...
46

You might also read

Related Articles

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

Sort by
Same author

Construction and Validation of Active Case-Finding Tool in Community Participants with Chronic Obstructive Pulmonary Disease Using an Interpretable Machine Learning Approach.

International journal of chronic obstructive pulmonary disease·2026
Same author

Adaptive geometric-attention multi-task framework with knowledge distillation for aortic dissection detection in non-contrast CT.

Physics in medicine and biology·2026
Same author

Alpha-synuclein structural variants driving tau pathology and disease interaction.

Neural regeneration research·2026
Same author

AI-Guided Dual Strategy for Peptide Inhibitor Design Targeting Structural Polymorphs of α-Synuclein Fibrils.

Cells·2025
Same author

AI-Guided Dual Strategy for Peptide Inhibitor Design Targeting Structural Polymorphs of α-Synuclein Fibrils.

bioRxiv : the preprint server for biology·2025
Same author

Multi-scale cancer driver gene prediction by flexible data selection and network topology guidance.

Journal of biomedical informatics·2025

Related Experiment Video

Updated: Oct 10, 2025

Time-Resolved, Dynamic Computed Tomography Angiography for Characterization of Aortic Endoleaks and Treatment Guidance via 2D-3D Fusion-Imaging
09:32

Time-Resolved, Dynamic Computed Tomography Angiography for Characterization of Aortic Endoleaks and Treatment Guidance via 2D-3D Fusion-Imaging

Published on: December 9, 2021

3.1K

A Cascaded Deep Learning Framework for Detecting Aortic Dissection Using Non-contrast Enhanced Computed Tomography.

Xiangyu Xiong, Xiuhong Guan, Chuanqi Sun

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 11, 2021
    PubMed
    Summary

    This study introduces a deep learning framework to create contrast-enhanced CT images from non-contrast scans, improving the detection of aortic dissection (AD). The novel method enhances diagnostic capabilities for this critical condition.

    More Related Videos

    Three-Dimensional Imaging of Aortic Tissues in Atherosclerosis
    09:55

    Three-Dimensional Imaging of Aortic Tissues in Atherosclerosis

    Published on: October 25, 2024

    1.1K
    Author Spotlight: Using Point-of-Care Ultrasound for Comprehensive Evaluation of the Abdominal Aorta
    07:12

    Author Spotlight: Using Point-of-Care Ultrasound for Comprehensive Evaluation of the Abdominal Aorta

    Published on: September 8, 2023

    3.1K

    Related Experiment Videos

    Last Updated: Oct 10, 2025

    Time-Resolved, Dynamic Computed Tomography Angiography for Characterization of Aortic Endoleaks and Treatment Guidance via 2D-3D Fusion-Imaging
    09:32

    Time-Resolved, Dynamic Computed Tomography Angiography for Characterization of Aortic Endoleaks and Treatment Guidance via 2D-3D Fusion-Imaging

    Published on: December 9, 2021

    3.1K
    Three-Dimensional Imaging of Aortic Tissues in Atherosclerosis
    09:55

    Three-Dimensional Imaging of Aortic Tissues in Atherosclerosis

    Published on: October 25, 2024

    1.1K
    Author Spotlight: Using Point-of-Care Ultrasound for Comprehensive Evaluation of the Abdominal Aorta
    07:12

    Author Spotlight: Using Point-of-Care Ultrasound for Comprehensive Evaluation of the Abdominal Aorta

    Published on: September 8, 2023

    3.1K

    Area of Science:

    • Medical Imaging
    • Artificial Intelligence
    • Cardiovascular Diseases

    Background:

    • Aortic dissection (AD) is a life-threatening condition with high mortality rates.
    • Accurate and timely diagnosis of AD is crucial for effective treatment.
    • Contrast-enhanced computed tomography (CE-CT) is vital for AD detection, but non-contrast CT (NCE-CT) is more accessible.

    Purpose of the Study:

    • To develop a method for synthesizing CE-CT images from NCE-CT images for improved AD detection.
    • To evaluate a cascaded deep learning framework for this image synthesis task.

    Main Methods:

    • A cascaded deep learning framework was proposed, integrating a 3D segmentation network and a synthetic network.
    • The 3D segmentation network identified the aorta in both NCE-CT and CE-CT images.
    • A conditional generative adversarial network (CGAN) was used to non-linearly map NCE-CT to CE-CT images within the segmented aortic region.

    Main Results:

    • The cascaded deep learning framework successfully synthesized CE-CT-like images from NCE-CT data.
    • The proposed framework demonstrated superior performance in detecting aortic dissection compared to using CGAN alone.
    • The results indicate the potential of deep learning for enhancing AD diagnosis using NCE-CT.

    Conclusions:

    • The cascaded deep learning framework offers a promising approach for synthesizing contrast-enhanced CT images from non-contrast scans.
    • This technique can aid in the detection of aortic dissection, potentially improving patient outcomes.
    • Further research can explore the clinical utility and broader applications of this AI-driven imaging method.