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

Computed Tomography01:10

Computed Tomography

7.7K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
7.7K
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

177
DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
177

You might also read

Related Articles

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

Sort by
Same author

Local bit-plane neighbour dissimilarity pattern in non-subsampled shearlet transform domain for bio-medical image retrieval.

Mathematical biosciences and engineering : MBE·2022
See all related articles

Related Experiment Video

Updated: Dec 10, 2025

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
05:05

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Published on: November 23, 2019

8.3K

3D-local oriented zigzag ternary co-occurrence fused pattern for biomedical CT image retrieval.

Rakcinpha Hatibaruah1, Vijay Kumar Nath1, Deepika Hazarika1

  • 1Department of Electronics and Communication Engineering, Tezpur University, Tezpur, India.

Biomedical Engineering Letters
|August 28, 2020
PubMed
Summary

A novel 3D descriptor, the three dimensional local oriented zigzag ternary co-occurrence fused pattern (3D-ZTP), enhances computed tomography (CT) image retrieval. This method captures detailed 3D texture information for superior performance.

Keywords:
CT imageCo-occurrenceFeature vectorImage retrievalTernary patternZigzag pattern

More Related Videos

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

1.9K
Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer
03:55

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer

Published on: June 9, 2023

831

Related Experiment Videos

Last Updated: Dec 10, 2025

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
05:05

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Published on: November 23, 2019

8.3K
Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

1.9K
Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer
03:55

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer

Published on: June 9, 2023

831

Area of Science:

  • Medical Imaging
  • Computer Vision
  • Image Processing

Background:

  • Computed Tomography (CT) image retrieval relies on effective feature descriptors.
  • Conventional 2D local pattern methods capture limited spatial information.
  • 3D texture analysis is crucial for accurate CT image retrieval.

Purpose of the Study:

  • To propose a novel 3D feature descriptor for enhanced CT image retrieval.
  • To improve the discriminative power and efficiency of CT image retrieval systems.
  • To address limitations of existing 2D local pattern-based approaches.

Main Methods:

  • Introduced the three dimensional local oriented zigzag ternary co-occurrence fused pattern (3D-ZTP) descriptor.
  • Employed a 3D zigzag sampling structure on multiscale Gaussian filtered CT images.
  • Calculated 3D local ternary patterns and fused co-occurrence information for texture representation.

Main Results:

  • The 3D-ZTP descriptor effectively captures both uniform and non-uniform texture patterns.
  • Multiscale analysis via Gaussian filtering preserves fine to coarse image details.
  • Experiments on NEMA and TCIA-CT databases showed superior retrieval precision and recall compared to existing methods.

Conclusions:

  • The proposed 3D-ZTP descriptor significantly outperforms traditional local pattern-based methods for CT image retrieval.
  • The 3D zigzag sampling and fusion scheme enhance feature distinctiveness and reduce dimensionality.
  • This descriptor offers a promising advancement for medical image retrieval applications.