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

Extraction: Advanced Methods00:56

Extraction: Advanced Methods

1.1K
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
1.1K
Anatomy of the Gastrointestinal System01:26

Anatomy of the Gastrointestinal System

2.8K
The human digestive system is an intricate and essential network for nutrient absorption and waste elimination. It encompasses the gastrointestinal (GI) tract and several accessory organs.
Here's a detailed walkthrough of this complex system:
2.8K
Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy01:26

Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy

417
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...
417
Gastrointestinal Motility Disorders01:20

Gastrointestinal Motility Disorders

1.2K
Gastrointestinal or GI motility disorders are characterized by irregular gastrointestinal tract movements, disrupting food transit from the mouth to the anus. They are caused by damage or dysfunction in gut muscles or nerves. These disorders can cause symptoms such as severe constipation, diarrhea, abdominal pain, and swallowing difficulties. Disorders can affect any segment of the GI tract and range widely in severity, from common conditions like GERD to life-threatening conditions like...
1.2K
Histology of the Gastrointestinal (GI) Tract01:20

Histology of the Gastrointestinal (GI) Tract

3.4K
The GI tract, from beginning to end, is made up of four continuous tissue layers that adjust their structure according to their specific roles. These layers, from innermost to outermost, are known as the mucosa, submucosa, muscularis, and serosa, which are continuous with the mesentery.
The mucosa is sometimes called a mucous membrane due to its mucus-secreting features. This membrane is composed of epithelium, which directly interacts with ingested substances, and the lamina propria, a layer...
3.4K
Effects of EDTA on End-Point Detection Methods01:18

Effects of EDTA on End-Point Detection Methods

662
Different methods, such as visual observance of metal-ion indicators, spectroscopic techniques, and potentiometric methods, can determine the endpoint of an EDTA titration.
In the visual method, metal-ion indicators (metallochromic dyes), which have distinct colors in their free and complex forms, are added to the mixture to signal the titration's end point. They form stable complexes with metal ions, but these complexes are weaker than the corresponding metal–EDTA complexes. As a...
662

You might also read

Related Articles

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

Sort by
Same author

An Automatic Gastrointestinal Polyp Detection System in Video Endoscopy Using Fusion of Color Wavelet and Convolutional Neural Network Features.

International journal of biomedical imaging·2017
Same author

Design and implementation of an efficient single layer five input majority voter gate in quantum-dot cellular automata.

SpringerPlus·2016
Same author

A new approach of presenting reversible logic gate in nanoscale.

SpringerPlus·2015
See all related articles

Related Experiment Video

Updated: Jan 31, 2026

Author Spotlight: A Reproductive Hysteroscopy Approach for Complete Endometrial Polyp Removal and Enhanced Endometrial Receptivity
03:01

Author Spotlight: A Reproductive Hysteroscopy Approach for Complete Endometrial Polyp Removal and Enhanced Endometrial Receptivity

Published on: August 2, 2024

2.0K

Gastrointestinal polyp detection in endoscopic images using an improved feature extraction method.

Mustain Billah1, Sajjad Waheed1

  • 1Department of Information and Communication Technology (ICT), Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.

Biomedical Engineering Letters
|January 4, 2019
PubMed
Summary

Early detection of gastrointestinal polyps, precursors to cancer, is crucial. This study introduces an improved computer-aided detection method using combined features for higher accuracy in identifying polyps during endoscopy.

Keywords:
Color wavelet featuresConvolutional neural network (CNN)Endoscopic imageImproved methodSupport vector machine (SVM)Video endoscopy

More Related Videos

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

23.2K
Author Spotlight: Optimizing Apoplast Protein Extraction for Efficient Recovery of Recombinant Proteins from Plant Cells
05:33

Author Spotlight: Optimizing Apoplast Protein Extraction for Efficient Recovery of Recombinant Proteins from Plant Cells

Published on: July 5, 2024

2.1K

Related Experiment Videos

Last Updated: Jan 31, 2026

Author Spotlight: A Reproductive Hysteroscopy Approach for Complete Endometrial Polyp Removal and Enhanced Endometrial Receptivity
03:01

Author Spotlight: A Reproductive Hysteroscopy Approach for Complete Endometrial Polyp Removal and Enhanced Endometrial Receptivity

Published on: August 2, 2024

2.0K
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

23.2K
Author Spotlight: Optimizing Apoplast Protein Extraction for Efficient Recovery of Recombinant Proteins from Plant Cells
05:33

Author Spotlight: Optimizing Apoplast Protein Extraction for Efficient Recovery of Recombinant Proteins from Plant Cells

Published on: July 5, 2024

2.1K

Area of Science:

  • Medical Imaging
  • Artificial Intelligence in Medicine
  • Gastroenterology

Background:

  • Gastrointestinal polyps are precancerous, making early detection vital for cancer prevention.
  • Video endoscopy is the primary diagnostic tool, but human error can lead to missed polyp detection.
  • Computer-aided detection (CAD) systems can enhance diagnostic accuracy and reduce miss rates.

Purpose of the Study:

  • To develop and evaluate an improved computer-aided method for detecting gastrointestinal polyps in endoscopic images.
  • To reduce the polyp miss detection rate and assist clinicians in identifying critical regions.
  • To combine complementary feature extraction techniques for enhanced polyp recognition.

Main Methods:

  • Extraction of color wavelet features and convolutional neural network (CNN) features from endoscopic images.
  • Training a support vector machine (SVM) classifier using the combined features.
  • Automatic marking of detected polyps in target endoscopic images.

Main Results:

  • The fusion of color wavelet and CNN features provides a highly representative image signature for polyps.
  • The proposed system achieved high performance metrics: 98.34% accuracy, 98.67% sensitivity, and 98.23% specificity.
  • ROC analysis confirmed superior accuracy compared to existing state-of-the-art methods.

Conclusions:

  • Combining color wavelet and CNN features with SVM offers an effective approach for gastrointestinal polyp detection.
  • The developed system significantly improves upon current methods, aiding in earlier and more accurate polyp identification.
  • This enhanced CAD system has the potential to reduce gastrointestinal cancer incidence through improved polyp surveillance.