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 Experiment Videos

Computed tomographic virtual colonoscopy computer-aided polyp detection in a screening population.

Ronald M Summers1, Jianhua Yao, Perry J Pickhardt

  • 1Diagnostic Radiology Department, Warren Grant Magnuson Clinical Center, National Institutes of Health, Bethesda, Maryland 20892-1182, USA. rms@nih.gov

Gastroenterology
|December 14, 2005
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Digital decoding tissue microenvironment heterogeneity from spatial proteomics through graph-enhanced transfer learning.

Cell systems·2026
Same author

Oxygen-Vacancy-Engineered Y<sub>2</sub>O<sub>3</sub>/CeO<sub>2</sub> Nanobrush Superlattices via Laser Heteroepitaxy: Toward High-Performance Memristors.

Small methods·2026
Same author

Single-cell transcriptomics and machine learning identify RNF144B and C5AR1 as immune-related molecular signatures and therapeutic targets in myocardial infarction.

Genes & genomics·2026
Same author

Cardiac targeting extracellular vesicles combined with quercetin co-delivery system enhances the therapeutic efficacy of myocardial infarction.

Biomaterials advances·2026
Same author

Scalable homology detection with ERAST.

Nature biotechnology·2026
Same author

Functional protein design and enhancement with ontology reinforcement iteration.

Nature communications·2026
Same journal

How important is fiber in the Crohn's disease story?

Gastroenterology·2026
Same journal

Reply to "Critical Appraisal of the Integrin αV-YAP-CTGF Axis in Congestive Hepatopathy".

Gastroenterology·2026
Same journal

Critical Appraisal of the Integrin αV-YAP-CTGF Axis in Congestive Hepatopathy.

Gastroenterology·2026
Same journal

A High-Risk Impaction: To Scope or to Stent First?

Gastroenterology·2026
Same journal

Epithelial FOXP3 orchestrates O-glycosylated IL-6 secretion to drive pancreatic fibrocarcinogenesis.

Gastroenterology·2026
Same journal

Reply to "Methodological Considerations on Neonatal Metabolomics and Future Inflammatory Bowel Disease".

Gastroenterology·2026
See all related articles

A computer-aided detection (CAD) program shows sensitivity comparable to optical colonoscopy for detecting colorectal polyps during CT virtual colonoscopy screening. This CAD system demonstrates reliable performance in identifying adenomas 8 mm or larger in asymptomatic individuals.

Area of Science:

  • Medical Imaging
  • Gastroenterology
  • Artificial Intelligence in Medicine

Background:

  • Computed tomographic (CT) virtual colonoscopy (CT colonography) polyp detection sensitivity varies.
  • This study evaluated a computer-aided polyp detection (CAD) program against optical colonoscopy for adenomatous colonic polyps detected via CT virtual colonoscopy.

Discussion:

  • The CAD program achieved 89.3% per-polyp and per-patient sensitivity for adenomas >= 1 cm.
  • False-positive rates for CAD were 2.1 per patient, detecting both carcinomas at 0.7 per patient.
  • CAD sensitivity was comparable to optical colonoscopy for adenomas >= 8 mm.

Key Insights:

  • CT virtual colonoscopy CAD demonstrates high sensitivity for adenomatous polyps >= 1 cm.
  • The CAD system's performance is comparable to optical colonoscopy for adenomas >= 8 mm.

Related Experiment Videos

  • CAD shows generalizability to new CT virtual colonoscopy data.
  • Outlook:

    • Further validation of CAD systems in diverse clinical settings is warranted.
    • Integration of CAD may enhance the accuracy and efficiency of colorectal cancer screening.
    • Future research could explore CAD's role in detecting smaller polyps and its impact on patient outcomes.