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

Computed Tomography01:10

Computed Tomography

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...
Ultrasonography01:17

Ultrasonography

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 a...
Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

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...

You might also read

Related Articles

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

Sort by
Same author

Cardiac Modulation by <i>Santolina chamaecyparissus</i> Aqueous Extract in a Rat Model of Mammary Carcinogenesis.

Current issues in molecular biology·2026
Same author

Characterization of HIV acquisitions during a large oral PrEP implementation study: insights from the ImPrEP study.

AIDS (London, England)·2026
Same author

Neutrophil-Lymphocyte-Platelet Ratio for Predicting Bacteremia in Immunosuppressed Cancer Patients: A Retrospective Diagnostic Accuracy Study.

Biomedicines·2026
Same author

Improving Diabetic Foot Care With Infrared Thermography and Artificial Intelligence: A Review.

Journal of diabetes science and technology·2026
Same author

Racial disparities in HIV incidence and PrEP non-adherence among gay, bisexual and other Men who have Sex with Men (MSM) and transgender women using oral PrEP in Brazil: Results from the ImPrEP study.

The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases·2026
Same author

Ultrasonographic Evaluation of Canine Hip Dysplasia: Comparison with FCI Radiographic Scoring System.

Veterinary sciences·2026
Same journal

Iron-Handling, Lipid-Oxygenation, and Hypoxia-Response Gene Expression in the Renal Cortex of Cats with Chronic Kidney Disease: An Analysis-Plan-Guided Secondary Analysis.

Veterinary sciences·2026
Same journal

Dominance of the E198A Mutation and Emergence of Co-Selection in Benzimidazole-Resistant <i>Haemonchus contortus</i> from Northwestern China.

Veterinary sciences·2026
Same journal

Intelligent Veterinary Disease Management Driven by Knowledge Graph for Conservation Breeding of Captive Forest Musk Deer.

Veterinary sciences·2026
Same journal

Clinical Outcomes of Once-Weekly Hypofractionated Intensity-Modulated Radiation Therapy with Concurrent α-Sulfoquinovosyl-Acylpropanediol for Modified Adams Stage 4 Canine Intranasal Tumors: A Retrospective Case Series.

Veterinary sciences·2026
Same journal

Impact of Dam Lactation Number on Colostrum Quality, Calf Growth, and Economic Performance in Holstein Cows.

Veterinary sciences·2026
Same journal

Effects of Dietary Composite Postbiotic Preparation on Growth Performance, Immune Function, and Gut Microbiota in Nubian Black Goats.

Veterinary sciences·2026
See all related articles

Related Experiment Video

Updated: Jun 25, 2026

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

901

Artificial Intelligence in Veterinary Imaging: An Overview.

Ana Inês Pereira1, Pedro Franco-Gonçalo1,2,3, Pedro Leite4

  • 1Department of Veterinary Science, University of Trás-os-Montes and Alto Douro (UTAD), 5000-801 Vila Real, Portugal.

Veterinary Sciences
|May 26, 2023
PubMed
Summary
This summary is machine-generated.

This study provides veterinarians with a guide to artificial intelligence (AI) and machine learning (ML) in veterinary medical imaging. It explains AI/ML concepts for automated image analysis and diagnosis support in animals.

Keywords:
artificial intelligencedeep learningmachine learningveterinary imaging

More Related Videos

Use of Three-Dimensional Imaging Reconstruction Software as a Training Tool for Cranial Vena Cava Venipuncture in the Ferret
04:18

Use of Three-Dimensional Imaging Reconstruction Software as a Training Tool for Cranial Vena Cava Venipuncture in the Ferret

Published on: July 15, 2025

563
Author Spotlight: Standardizing Mouse In Vivo PET Imaging with Body Conforming Molds and Automated Analysis
07:45

Author Spotlight: Standardizing Mouse In Vivo PET Imaging with Body Conforming Molds and Automated Analysis

Published on: October 25, 2024

428

Related Experiment Videos

Last Updated: Jun 25, 2026

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

901
Use of Three-Dimensional Imaging Reconstruction Software as a Training Tool for Cranial Vena Cava Venipuncture in the Ferret
04:18

Use of Three-Dimensional Imaging Reconstruction Software as a Training Tool for Cranial Vena Cava Venipuncture in the Ferret

Published on: July 15, 2025

563
Author Spotlight: Standardizing Mouse In Vivo PET Imaging with Body Conforming Molds and Automated Analysis
07:45

Author Spotlight: Standardizing Mouse In Vivo PET Imaging with Body Conforming Molds and Automated Analysis

Published on: October 25, 2024

428

Area of Science:

  • Veterinary Medical Imaging
  • Artificial Intelligence in Medicine
  • Machine Learning Applications

Background:

  • Medical image evaluation is subjective and complex, necessitating automated analysis.
  • Artificial intelligence (AI) and machine learning (ML) offer solutions for objective image interpretation.
  • Existing research applies AI/ML to assist veterinary diagnostics.

Purpose of the Study:

  • To provide veterinary professionals with a foundational understanding of AI and ML.
  • To detail methodologies for developing AI/ML software for veterinary medical imaging.
  • To review existing literature on AI/ML applications in animal imaging diagnosis.

Main Methods:

  • Explanation of core AI/ML concepts: deep learning, convolutional neural networks, transfer learning.
  • Review of published research on AI/ML in veterinary imaging diagnosis.
  • Focus on practical application and benefit for veterinarians.

Main Results:

  • The study outlines methodologies for creating AI/ML-powered diagnostic tools.
  • It covers applications across various animal body systems: musculoskeletal, thoracic, nervous, and abdominal.
  • The guide is tailored for veterinary technicians and professionals.

Conclusions:

  • AI and ML methodologies can significantly enhance the accuracy and efficiency of veterinary medical imaging analysis.
  • This guide empowers veterinarians to leverage AI/ML for improved diagnostic capabilities.
  • Understanding these technologies is crucial for the future of veterinary diagnostics.