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

Radiological Investigation I: X-ray and CT01:30

Radiological Investigation I: X-ray and CT

269
Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and...
269
X-ray Imaging01:24

X-ray Imaging

5.6K
German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
5.6K
Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

206
The most common cardiovascular diagnostic test is an X-ray. It produces images of the heart, blood vessels, and adjacent structures.
Definition and Purpose
An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...
206
Computed Tomography01:10

Computed Tomography

4.6K
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...
4.6K

You might also read

Related Articles

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

Sort by
Same author

Detection, localization, and measurement of endotracheal tube positioning on adults' chest X-ray: developing a prediction model.

Scientific reports·2026
Same author

Vascular Endothelial Function, Carotid Intima-Media Thickness and Coronary Artery Calcification in Women.

Journal of clinical medicine·2026
Same author

Nontechnical Skills (NTS) and the Quality of Conducting Prehospital Advanced Cardiopulmonary Resuscitation Among Paramedics.

Emergency medicine international·2026
Same author

Correction to: Accuracy of vestibular schwannoma segmentation using deep learning models - a systematic review & meta-analysis.

Neuroradiology·2026
Same author

Correction: Sharper vision, steady hands: can robots improve subretinal drug delivery? Systematic review.

Journal of robotic surgery·2026
Same author

Retraction Note: An early evaluation of robot-assisted and conventional techniques for posterior approach atlantoaxial displacement instrumentation - a systematic review and meta-analysis.

Neurosurgical review·2026

Related Experiment Video

Updated: Jul 15, 2025

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

879

Chest X-ray Foreign Objects Detection Using Artificial Intelligence.

Jakub Kufel1, Katarzyna Bargieł-Łączek2,3, Maciej Koźlik4

  • 1Department of Biophysics, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Jordana 19, 41-808 Zabrze, Poland.

Journal of Clinical Medicine
|September 28, 2023
PubMed
Summary

This study developed an AI tool using deep learning to detect foreign objects like vascular ports and ICDs on chest X-rays. The model achieved 0.815 average precision, aiding faster radiological diagnoses.

Keywords:
artifactsartificial intelligencechest X-rayconvolutional neural networkforeign body

More Related Videos

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.9K
Artificial Intelligence Approaches to Assessing Primary Cilia
08:58

Artificial Intelligence Approaches to Assessing Primary Cilia

Published on: May 1, 2021

3.5K

Related Experiment Videos

Last Updated: Jul 15, 2025

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

879
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.9K
Artificial Intelligence Approaches to Assessing Primary Cilia
08:58

Artificial Intelligence Approaches to Assessing Primary Cilia

Published on: May 1, 2021

3.5K

Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Computer Vision

Background:

  • Diagnostic imaging is crucial for healthcare, with AI tools enhancing diagnostic speed and accuracy.
  • Accurate detection of foreign objects in medical images is vital for patient treatment.
  • The increasing workload in radiology necessitates efficient diagnostic support tools.

Purpose of the Study:

  • To develop and evaluate a deep convolutional neural network for detecting specific foreign objects on digital chest X-ray images.
  • To assess the accuracy of an AI model in identifying vascular ports, shoulder endoprostheses, necklaces, and implantable cardioverter-defibrillators (ICDs) in chest X-rays.

Main Methods:

  • Utilized the National Institutes of Health (NIH) Chest X-ray (CXR) Dataset comprising 112,120 images from 30,805 patients.
  • Manually annotated CXRs for four foreign object categories: vascular port, shoulder endoprosthesis, necklace, and implantable cardioverter-defibrillator (ICD).
  • Trained an object detection model using the You Only Look Once v8 (YOLOv8) architecture and the Ultralytics framework, including image preprocessing steps like resizing, normalization, and cropping.

Main Results:

  • The AI model achieved an average precision of 0.815 for foreign object detection on chest X-ray images.
  • Demonstrated the model's utility and effectiveness in identifying various foreign objects within CXR scans.
  • The developed model shows potential as a supportive tool for radiologists, particularly given the increasing demands in the field.

Conclusions:

  • The deep convolutional neural network effectively detects foreign objects on chest X-rays with high accuracy.
  • AI-powered diagnostic tools can significantly accelerate and facilitate the work of radiologists.
  • This technology holds promise for improving the efficiency and speed of radiological diagnoses.