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

Automatic background recognition and removal (ABRR) in computed radiography images

J Zhang1, H K Huang

  • 1Department of Radiology, University of California, San Francisco 94143-0628, USA. jianguo-zhang@radmacl.ucsf.edu

IEEE Transactions on Medical Imaging
|April 9, 1998
PubMed
Summary

A new method accurately identifies and removes X-ray collimation background in computed radiography (CR) images. This automated process achieves high accuracy, improving image quality for diagnostic purposes.

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

[Effects of Shugan Jieyu capsules combined with Zolpidem on sleep quality and daytime cognitive function in insomnia with depressive symptoms patients].

Zhonghua yi xue za zhi·2025
Same author

Medical imaging, PACS, and imaging informatics: retrospective.

Radiological physics and technology·2013
Same author

Medical imaging informatics simulators: a tutorial.

International journal of computer assisted radiology and surgery·2013
Same author

A DICOM-based 2nd generation Molecular Imaging Data Grid implementing the IHE XDS-i integration profile.

International journal of computer assisted radiology and surgery·2011
Same author

From PACS to Web-based ePR system with image distribution for enterprise-level filmless healthcare delivery.

Radiological physics and technology·2011
Same author

Short history of PACS. Part I: USA.

European journal of radiology·2011

Area of Science:

  • Medical Imaging
  • Radiography
  • Image Processing

Background:

  • Computed radiography (CR) images often contain background signals from X-ray collimation.
  • These signals can obscure diagnostic information and affect image quality.
  • Automated methods are needed for efficient and reliable background removal.

Purpose of the Study:

  • To develop and evaluate a novel automated method for recognizing and removing background signals in CR images.
  • To improve the diagnostic quality of CR images by eliminating artifacts caused by X-ray collimation.

Main Methods:

  • A three-step approach involving statistical curve derivation, signal processing (sampling, filtering, angle recognition), and adaptive parameter adjustments.
  • Edge detection and background removal algorithms were developed and refined.

Related Experiment Videos

  • The method was implemented in a clinical picture archiving and communication system (PACS).

    • Main Results:

    • Achieved 99% correct recognition of CR image background.
    • Successfully removed 91% of the background without affecting valid image data.
    • Demonstrated reliable background removal in a clinical setting.

    Conclusions:

    • The novel automated method effectively removes X-ray collimation background from CR images.
    • This technique significantly enhances CR image quality and diagnostic utility.
    • The method shows high accuracy and reliability for clinical implementation.