Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy

Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy

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...

Protein Folding

Protein Folding

Protein Folding Quality Check in the RER

Protein Folding Quality Check in the RER

ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...

Endoscopic Procedures II: Colonoscopy

Endoscopic Procedures II: Colonoscopy

The colon, or large intestine, is the final segment of the digestive system. Its primary functions include absorbing water and vitamins produced by gut bacteria and transforming waste from liquid to solid to form stool. In adults, the large intestine is approximately 5 feet long and consists of four main sections:

You might also read

Related Articles

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

Sort by

Same author

Serum Albumin, Globulin and Albumin-Globulin Ratios as Biomarkers of Clinical Outcomes in COVID-19 Pneumonia.

Journal of personalized medicine·2026

Same author

RT-GAN: Recurrent Temporal GAN for Adding Lightweight Temporal Consistency to Frame-Based Domain Translation Approaches.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026

Same author

Recycling and Environmental Sustainability in Anesthesia Practice: Beyond Low‑Flow Anesthesia.

Cureus·2026

Same author

Tumor Microenvironment: Insights from Multiparametric MRI in Pancreatic Ductal Adenocarcinoma.

Cancers·2026

Same author

Whole Slide Imaging in Genitourinary Pathology:<br /> A Cloud-Based Digitisation Workflow for Resource-Limited Settings.

Journal of the College of Physicians and Surgeons--Pakistan : JCPSP·2025

Same author

Healthcare Utilization Unchanged in the Control Arm of a Randomized Clinical Trial.

Journal of primary care & community health·2025

Search research articles

Related Experiment Video

Updated: Sep 27, 2025

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

Published on: January 2, 2012

FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos.

Shawn Mathew¹, Saad Nadeem², Arie Kaufman¹

¹Department of Computer Science, Stony Brook University.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

|April 11, 2022

Summary

Accurate segmentation of haustral folds in colonoscopy videos improves polyp detection and aids navigation. Our novel FoldIt network translates optical colonoscopy images to virtual renderings, enhancing visualization of these critical structures.

Keywords:

Colonoscopy Haustral Folds Segmentation

More Related Videos

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Published on: April 8, 2019

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

Related Experiment Videos

Last Updated: Sep 27, 2025

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

Published on: January 2, 2012

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Published on: April 8, 2019

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

Area of Science:

Medical Imaging
Computer Vision
Gastroenterology

Background:

Haustral folds in colonoscopy increase polyp miss rates.
Accurate haustral fold segmentation can improve surface area estimation.
These folds serve as landmarks for registering optical and virtual colonoscopies.

Purpose of the Study:

To develop a novel generative adversarial network (FoldIt) for accurate haustral fold segmentation.
To enable feature-consistent image translation from optical to virtual colonoscopy renderings.
To improve navigation and anomaly detection in colonoscopy procedures.

Main Methods:

A novel generative adversarial network, FoldIt, was developed.
A transitive loss function was introduced to leverage ground truth data.
The model was trained and validated on real and simulated colonoscopy videos.

Main Results:

FoldIt demonstrated effective feature-consistent image translation.
The model successfully generated virtual colonoscopy renderings with haustral fold overlays.
Performance was validated on challenging real-world and textured virtual colonoscopy data.

Conclusions:

Haustral fold segmentation using FoldIt enhances colonoscopy navigation and anomaly detection.
The developed method aids in registering pre-treatment virtual and optical colonoscopies.
This approach has the potential to reduce polyp miss rates and improve patient outcomes.