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

Ultrasonography01:17

Ultrasonography

4.7K
Ultrasonography is an imaging technique that uses high-frequency sound waves to visualize the body's internal structures. It is a non-invasive and safe procedure that does not involve the use of ionizing radiation, making it widely used in various medical fields. Ultrasonography is used to study heart function, blood flow in the neck or extremities, certain conditions such as gallbladder disease, and fetal growth and development.
During an ultrasonography procedure, a handheld device called...
4.7K
Ultrasound II: Endoscopic Ultrasound and FibroScan01:25

Ultrasound II: Endoscopic Ultrasound and FibroScan

156
Endoscopic Ultrasound (EUS) and FibroScan are valuable diagnostic tools in gastroenterology and hepatology, each with specific applications and techniques.
Endoscopic Ultrasound (EUS):
156

You might also read

Related Articles

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

Sort by
Same author

ReGrid: A Highly Conformable and Ultrasound Transparent Patch for HD-sEMG Detection.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same author

Compressed Sensing of Acoustic Cardiopulmonary Signals Using a CNN-based Reconstruction Method.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Left ventriculo-arterial coupling in a contemporary cohort of patients with wild-type transthyretin cardiac amyloidosis treated with tafamidis.

Clinical research in cardiology : official journal of the German Cardiac Society·2025
Same author

High-Sensitivity Cardiac Troponin I for Risk Stratification in Wild-Type Transthyretin Amyloid Cardiomyopathy.

Circulation. Heart failure·2025
Same author

Emerging Applications of Augmented and Mixed Reality Technologies in Motor Rehabilitation: A Scoping Review.

Sensors (Basel, Switzerland)·2025
Same author

A 3D-Printed Educational Model for First-Line Management of BPPV in Emergency Departments.

Audiology research·2024

Related Experiment Video

Updated: Aug 5, 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

Perceptive SARS-CoV-2 End-To-End Ultrasound Video Classification through X3D and Key-Frames Selection.

Marco Gazzoni1, Marco La Salvia1, Emanuele Torti1

  • 1Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy.

Bioengineering (Basel, Switzerland)
|March 29, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a deep learning approach for diagnosing pneumonia using Lung Ultrasound (LUS) videos. The method accurately classifies SARS-CoV-2 severity, achieving an F1-Score over 89% for reliable, rapid medical diagnosis.

Keywords:
Lung UltrasoundSARS-CoV-2deep learningvideo classification

More Related Videos

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

9.0K
Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

2.1K

Related Experiment Videos

Last Updated: Aug 5, 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
Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

9.0K
Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

2.1K

Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Pulmonology

Background:

  • The SARS-CoV-2 pandemic highlighted the need for rapid and reliable diagnostic tools for pneumonia.
  • Lung Ultrasound (LUS) offers a radiation-free alternative to Chest X-rays (CXR) and Computed Tomography (CT) scans, but its utilization is limited by the need for specialized expertise.
  • Deep learning (DL) has shown promise in analyzing medical images, including LUS, for disease detection.

Purpose of the Study:

  • To develop and evaluate a DL-based video-classification approach for diagnosing and assessing the severity of SARS-CoV-2 pneumonia using LUS.
  • To address limitations of existing methods by focusing on video analysis rather than static frame patterns.
  • To implement a standardized severity ranking scale for pneumonia evaluation based on LUS findings.

Main Methods:

  • A dataset of 5400 LUS video clips from 450 hospitalized patients was utilized.
  • Key-frame selection algorithms were employed for video summarization.
  • A novel video-classification architecture was designed and developed, incorporating transfer learning and data augmentation techniques.

Main Results:

  • The developed DL model achieved an F1-Score exceeding 89% across all severity classification classes.
  • The approach demonstrated effectiveness in detecting SARS-CoV-2 patterns and ranking pneumonia severity.
  • The method showed strong correlation and reliability in pneumonia detection, comparable to established imaging modalities.

Conclusions:

  • The proposed LUS video-classification approach offers a promising, accurate, and efficient tool for diagnosing and grading pneumonia, particularly in the context of SARS-CoV-2.
  • This DL-based strategy enhances the utility of LUS, potentially improving clinical decision-making and patient outcomes.
  • The study underscores the potential of advanced DL techniques in medical video analysis for critical care settings.