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

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

5.8K
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
5.8K
Ultrasonography01:17

Ultrasonography

5.1K
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...
5.1K
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.8K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.8K
Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

417
Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...
417

You might also read

Related Articles

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

Sort by
Same author

Application of LLMs in CAD-RADS Classification and Patient Management.

Echocardiography (Mount Kisco, N.Y.)·2026
Same author

Diagnostic accuracy of third-generation dual-source dual-energy CT virtual non-contrast vs true non-contrast imaging in adrenal gland masses: a comparative study following the ACR guidelines.

La Radiologia medica·2026
Same author

Independent prognostic value of left ventricular stroke volume index in patients with takotsubo syndrome: insights from the EVOLUTION registry.

Heart (British Cardiac Society)·2026
Same author

Radiology appointment management in German hospitals: a survey of referring physicians.

Insights into imaging·2026
Same author

Gravitational 3D Magnetic Resonance Elastography for Differentiating Focal Nodular Hyperplasia and Hepatic Adenoma.

Diagnostics (Basel, Switzerland)·2026
Same author

Improving aortic calcium assessment in contrast-enhanced CT: exploring Hounsfield Unit thresholds for cardiovascular scoring.

La Radiologia medica·2026

Related Experiment Video

Updated: Aug 29, 2025

A Novel Application of Musculoskeletal Ultrasound Imaging
10:53

A Novel Application of Musculoskeletal Ultrasound Imaging

Published on: September 17, 2013

24.2K

Artificial intelligence, machine learning and deep learning in musculoskeletal imaging: Current applications.

Tommaso D'Angelo1,2, Danilo Caudo1,3, Alfredo Blandino1

  • 1Department of Biomedical Sciences and Morphological and Functional Imaging, University Hospital Messina, Messina, Italy.

Journal of Clinical Ultrasound : JCU
|September 7, 2022
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) shows significant potential in medical diagnostics, particularly in imaging. This review explores AI, machine learning, and deep learning applications for managing complex medical data and diagnosing musculoskeletal disorders.

Keywords:
artificial intelligencedeep learningmachine learningmusculoskeletal imaging

More Related Videos

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K
3D Ultrasound Imaging: Fast and Cost-effective Morphometry of Musculoskeletal Tissue
08:52

3D Ultrasound Imaging: Fast and Cost-effective Morphometry of Musculoskeletal Tissue

Published on: November 27, 2017

23.3K

Related Experiment Videos

Last Updated: Aug 29, 2025

A Novel Application of Musculoskeletal Ultrasound Imaging
10:53

A Novel Application of Musculoskeletal Ultrasound Imaging

Published on: September 17, 2013

24.2K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K
3D Ultrasound Imaging: Fast and Cost-effective Morphometry of Musculoskeletal Tissue
08:52

3D Ultrasound Imaging: Fast and Cost-effective Morphometry of Musculoskeletal Tissue

Published on: November 27, 2017

23.3K

Area of Science:

  • Medical technology
  • Computer science
  • Radiology

Background:

  • Artificial intelligence (AI) is increasingly integrated into various technological fields.
  • The medical sector, especially diagnostic imaging, demonstrates substantial developmental potential for AI.
  • AI simulates human intelligence to manage complex problems, with applications ranging from data handling to diagnostics.

Purpose of the Study:

  • To review the technical foundations of artificial intelligence, machine learning, and deep learning.
  • To illustrate the potential of AI applications in medical imaging workflows, including request management, data acquisition, image reconstruction, and archiving.
  • To discuss dedicated AI tools for segmentation, lesion detection, automatic diagnosis, and classification of musculoskeletal disorders.

Main Methods:

  • Review of technical background in artificial intelligence, machine learning, and deep learning.
  • Exploration of AI applications in medical imaging processes.
  • Discussion of AI tools for musculoskeletal disorder analysis.

Main Results:

  • AI offers broad potential in managing medical imaging workflows, from data acquisition to archiving and communication.
  • Dedicated AI tools show promise for segmentation, lesion detection, and automated diagnosis in musculoskeletal imaging.
  • AI facilitates the classification of musculoskeletal disorders.

Conclusions:

  • Artificial intelligence, machine learning, and deep learning are transformative technologies in medical diagnostics.
  • AI applications can optimize various aspects of diagnostic imaging, improving efficiency and accuracy.
  • AI tools are poised to enhance the diagnosis and classification of musculoskeletal disorders.