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

Part-based local shape models for colon polyp detection.

Rahul Bhotika1, Paulo R S Mendonça, Saad A Sirohey

  • 1GE Global Research, One Research Circle, Niskayuna, NY 12309, USA. bhotika@research.ge.com

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|March 16, 2007
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

Open-source Software Sustainability Models: Initial White Paper From the Informatics Technology for Cancer Research Sustainability and Industry Partnership Working Group.

Journal of medical Internet research·2021
Same author

ACTIVE LEARNING GUIDED INTERACTIONS FOR CONSISTENT IMAGE SEGMENTATION WITH REDUCED USER INTERACTIONS.

Proceedings. IEEE International Symposium on Biomedical Imaging·2019
Same author

Detection of adulterated drugs in traditional Chinese medicine and dietary supplements using hydrogen as a carrier gas.

PloS one·2018
Same author

Determination of multiresidue analysis of β-agonists in muscle and viscera using liquid chromatograph/tandem mass spectrometry with Quick, Easy, Cheap, Effective, Rugged, and Safe methodologies.

Journal of food and drug analysis·2017
Same author

Bolus arrival time and its effect on tissue characterization with dynamic contrast-enhanced magnetic resonance imaging.

Journal of medical imaging (Bellingham, Wash.)·2016
Same author

BRAIN TUMOR SEGMENTATION WITH SYMMETRIC TEXTURE AND SYMMETRIC INTENSITY-BASED DECISION FORESTS.

Proceedings. IEEE International Symposium on Biomedical Imaging·2014

This study introduces a novel model-based technique for detecting colon lesions in CT scans using analytical shape models. The method accurately labels voxels, improving polyp and fold detection for better colon cancer screening.

Area of Science:

  • Medical Imaging
  • Computer-Aided Diagnosis
  • Radiology

Background:

  • Current methods for colon lesion detection in CT scans often rely on intensity profiles and basic shape analysis.
  • Discriminating complex anatomical structures like colon folds and polyps using simple geometric models remains challenging.
  • A need exists for more sophisticated model-based approaches to accurately analyze colon CT data.

Purpose of the Study:

  • To present a novel model-based technique for lesion detection in colon CT scans.
  • To introduce analytical shape models specifically designed for colon anatomy, including folds and polyps.
  • To develop a simple voxel labeling scheme for classifying anatomical structures within CT volumes.

Main Methods:

  • Development of novel analytical shape models by combining simpler geometric shapes to represent colon folds and polyps.

Related Experiment Videos

  • Mapping local shape curvature at individual voxels to anatomical labels using these models.
  • Derivation of all parameters from analytical models for a straightforward voxel classification scheme.

    • Main Results:

    • The proposed analytical shape models provide a better approximation of actual colon anatomical structures.
    • The model-based analysis on simpler geometric parts enables effective discrimination of complex shapes.
    • Performance evaluation on 42 scans against expert ground truth, quantified using free-response receiver-operator curves.

    Conclusions:

    • The developed model-based technique offers a promising approach for accurate lesion detection in colon CT scans.
    • The novel analytical shape models enhance the ability to analyze and classify colon-specific anatomy.
    • This method facilitates improved computer-aided diagnosis for colorectal pathologies.