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

Endoscopic Procedures III: Video Capsule Endoscopy01:28

Endoscopic Procedures III: Video Capsule Endoscopy

372
Capsule endoscopy, or wireless or video capsule endoscopy, is a diagnostic procedure for examining the entire gastrointestinal tract. Patients swallow a capsule about the size of a vitamin tablet. The capsule is equipped with a transmitter, a battery, an LED light source, and a color video camera to capture images throughout the gastrointestinal tract. This procedure is particularly useful for diagnosing conditions such as Crohn's disease, ulcerative colitis, tumors, polyps, ulcers,...
372
Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy01:26

Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy

176
This lesson explores three gastrointestinal imaging techniques: radionuclide testing, colonic transit studies, and virtual colonoscopy.
Radionuclide Testing
Radionuclide testing is a sophisticated medical technique for assessing gastrointestinal motility. It focuses on gastric emptying and colonic transit time. Radioactive markers track the movement of food through the digestive system, providing insights into gastrointestinal disorders.
In gastric emptying studies, a meal's liquid and...
176

You might also read

Related Articles

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

Sort by
Same author

Early thermal pulses drive interfacial pre-aging and plastisphere pre-shaping: An overlooked pre-conditioning pathway in PLA microplastic aging during composting.

Journal of hazardous materials·2026
Same author

Environment-Responsive Sustained-Release Nanoparticles for the Protection, Delivery and Release of Clove Essential Oil to Improve Foodborne Bacterial Colitis Treatment.

Advanced healthcare materials·2026
Same author

Redesign of the Ferritin Ferroxidase Center for Universal Molecular Binding or Specific Recognition.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Virtual sailing exercise enhances motor performance while maintaining stable mental and neurochemical profiles in healthy adults: a pilot study.

Frontiers in physiology·2026
Same author

Corrigendum to "Thermally driven polymer disentanglement: An overlooked Key pathway in PBAT-microplastic aging during composting" [J Hazard Mater 503 (2026) 141080].

Journal of hazardous materials·2026
Same author

Printed Microscale Photonic Resonant Structured Photodetectors for Monitoring Eye Movement Abnormalities.

ACS sensors·2026

Related Experiment Video

Updated: Oct 13, 2025

Murine Endoscopy for In Vivo Multimodal Imaging of Carcinogenesis and Assessment of Intestinal Wound Healing and Inflammation
09:42

Murine Endoscopy for In Vivo Multimodal Imaging of Carcinogenesis and Assessment of Intestinal Wound Healing and Inflammation

Published on: August 26, 2014

18.9K

Single Shot Multibox Detector Automatic Polyp Detection Network Based on Gastrointestinal Endoscopic Images.

Xiaoling Chen1, Kuiling Zhang1, Shuying Lin2

  • 1Department of Gastroenterology, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, Fujian 362000, China.

Computational and Mathematical Methods in Medicine
|November 15, 2021
PubMed
Summary

This study introduces an automatic polyp detection algorithm using Single Shot Multibox Detector (SSD) for gastrointestinal images. The SSD model significantly improves detection accuracy and speed compared to manual methods and Mask R-CNN.

More Related Videos

Studying Murine Small Bowel Mechanosensing of Luminal Particulates
10:21

Studying Murine Small Bowel Mechanosensing of Luminal Particulates

Published on: March 18, 2022

2.0K
Author Spotlight: Generation of and Comparison Between Patient-Derived Gastric Organoids from Different Regions of the Stomach
08:45

Author Spotlight: Generation of and Comparison Between Patient-Derived Gastric Organoids from Different Regions of the Stomach

Published on: January 26, 2024

1.6K

Related Experiment Videos

Last Updated: Oct 13, 2025

Murine Endoscopy for In Vivo Multimodal Imaging of Carcinogenesis and Assessment of Intestinal Wound Healing and Inflammation
09:42

Murine Endoscopy for In Vivo Multimodal Imaging of Carcinogenesis and Assessment of Intestinal Wound Healing and Inflammation

Published on: August 26, 2014

18.9K
Studying Murine Small Bowel Mechanosensing of Luminal Particulates
10:21

Studying Murine Small Bowel Mechanosensing of Luminal Particulates

Published on: March 18, 2022

2.0K
Author Spotlight: Generation of and Comparison Between Patient-Derived Gastric Organoids from Different Regions of the Stomach
08:45

Author Spotlight: Generation of and Comparison Between Patient-Derived Gastric Organoids from Different Regions of the Stomach

Published on: January 26, 2024

1.6K

Area of Science:

  • Medical Imaging
  • Computer Vision
  • Artificial Intelligence

Background:

  • Gastrointestinal polyp diagnosis relies on expert pathological analysis of endoscopic images.
  • High missed and misdiagnosis rates present a significant clinical challenge.

Purpose of the Study:

  • To develop an automatic polyp detection algorithm to improve diagnostic accuracy.
  • To address limitations in current manual pathological analysis of gastrointestinal endoscopic images.

Main Methods:

  • An automatic polyp detection algorithm based on the Single Shot Multibox Detector (SSD) framework was developed.
  • The SSD model utilized a VGG-16 base with modifications to convolutional layers and added scale layers.
  • Performance was evaluated against manual polyp detection and the Mask R-CNN algorithm.

Main Results:

  • The SSD network achieved a mean Average Precision (mAP) of 95.74%.
  • This represents a 12.4% improvement over manual detection and a 5.7% improvement over Mask R-CNN.
  • SSD demonstrated a detection speed 8.41 times faster than manual detection per image frame.

Conclusions:

  • Deep learning algorithms, including SSD, show significant potential for gastrointestinal image recognition.
  • The proposed algorithm offers efficient and accurate polyp detection, aiding in reducing diagnostic errors.