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Related Concept Videos

Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy01:26

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 solid...

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Related Experiment Video

Updated: May 25, 2026

Flexible Colonoscopy in Mice to Evaluate the Severity of Colitis and Colorectal Tumors Using a Validated Endoscopic Scoring System
15:49

Flexible Colonoscopy in Mice to Evaluate the Severity of Colitis and Colorectal Tumors Using a Validated Endoscopic Scoring System

Published on: October 16, 2013

Distributed human intelligence for colonic polyp classification in computer-aided detection for CT colonography.

Tan B Nguyen1, Shijun Wang, Vishal Anugu

  • 1Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD 20892-1182, USA.

Radiology
|January 26, 2012
PubMed
Summary
This summary is machine-generated.

Distributed human intelligence shows comparable diagnostic performance to computer-aided detection (CAD) for classifying colonic polyps in computed tomographic (CT) colonography. This crowdsourced approach offers a viable alternative for polyp detection, particularly for easier cases.

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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Published on: July 11, 2025

Related Experiment Videos

Last Updated: May 25, 2026

Flexible Colonoscopy in Mice to Evaluate the Severity of Colitis and Colorectal Tumors Using a Validated Endoscopic Scoring System
15:49

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Published on: October 16, 2013

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Area of Science:

  • Medical imaging and diagnostics
  • Artificial intelligence in healthcare
  • Gastroenterology

Background:

  • Computer-aided detection (CAD) systems are used to identify potential polyps in computed tomographic (CT) colonography.
  • Assessing the diagnostic performance of human intelligence, particularly when distributed through crowdsourcing, is crucial for refining these systems.

Purpose of the Study:

  • To evaluate the diagnostic accuracy of distributed human intelligence in classifying polyp candidates detected by CAD in CT colonography.
  • To compare the performance of human intelligence against CAD for colonic polyp classification.

Main Methods:

  • 268 polyp candidates from CT colonography images of 24 patients were identified using CAD.
  • Twenty knowledge workers (KWs) from a crowdsourcing platform classified these candidates in two trials.
  • Performance was measured using the area under the receiver operating characteristic curve (AUC) and compared between KWs and CAD.

Main Results:

  • The detection-level AUC for KWs was 0.845 in trial 1 and 0.855 in trial 2, not significantly different from CAD's AUC of 0.859.
  • KWs outperformed CAD on easier polyp detections (AUCs 0.951-0.966 vs. 0.877).
  • KWs participating in both trials showed significant performance improvement from trial 1 (AUC 0.759) to trial 2 (AUC 0.839).

Conclusions:

  • Distributed human intelligence demonstrates diagnostic performance comparable to CAD for colonic polyp classification.
  • Crowdsourced human intelligence is a promising tool for polyp detection in CT colonography, especially for simpler cases.
  • Further research can explore optimizing the integration of human intelligence with CAD for enhanced colorectal cancer screening.