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

Developing a distributed collaborative radiological visualization application.

Justin Binns1, Fred Dech, Matthew McCrory

  • 1Mathematics and Computer Science Division, Argonne National Laboratory.

Studies in Health Technology and Informatics
|June 1, 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

The HuBMAP Framework for Advancing Data FAIRness.

bioRxiv : the preprint server for biology·2026
Same author

The Common Fund Data Ecosystem (CFDE).

bioRxiv : the preprint server for biology·2026
Same author

Do machine learning models add value in assessing operative stress?

Surgery·2026
Same author

SenNet Portal: Build, Optimization and Usage.

bioRxiv : the preprint server for biology·2026
Same author

CACHE Challenge #3: Targeting the Nsp3 Macrodomain of SARS-CoV-2.

Journal of chemical information and modeling·2026
Same author

Predicting Alzheimer's Disease Diagnosis, a Decade or more Years before Onset using the Electronic Health Record and Random Forest Machine Learning Models.

medRxiv : the preprint server for health sciences·2025
Same journal

The Essential Components and Critical Conditions for Success in a Learning Health System in Oncology.

Studies in health technology and informatics·2026
Same journal

Use of Artificial Intelligence in Screening for Adolescent Idiopathic Scoliosis: A Scoping Review.

Studies in health technology and informatics·2026
Same journal

Movement Related Biomechanics in Adolescent Idiopathic Scoliosis: A Review of Reviews.

Studies in health technology and informatics·2026
Same journal

The Impact of Surgical Correction of Adolescent Idiopathic Scoliosis Using Posterior Spinal Fusion on Selected Radiological Parameters and Respiratory Function.

Studies in health technology and informatics·2026
Same journal

Acute Effect of Physio-logic® Exercises on Muscle Tone and Stiffness in Adolescent Idiopathic Scoliosis Patients: A Preliminary Study.

Studies in health technology and informatics·2026
Same journal

Effects of Integrated Music and Occupational Therapy on Motor and Autonomic Function in Children with Neurogenic Scoliosis.

Studies in health technology and informatics·2026
See all related articles

This study presents a flexible system for distributed collaborative radiological visualization. It utilizes modern graphics hardware and web technologies to enhance medical imaging applications.

Area of Science:

  • Medical Imaging
  • Computer Science
  • Visualization

Background:

  • Current radiological visualization tools often lack distributed collaborative capabilities.
  • Advances in commodity graphics hardware and web technologies present opportunities for improved solutions.

Purpose of the Study:

  • To design a flexible system for constructing distributed collaborative radiological visualization applications.
  • To leverage existing hardware and software standards for a robust solution.

Main Methods:

  • Utilized advances in commodity graphics hardware.
  • Integrated community-proven collaboration technology.
  • Employed standard Web and Grid technologies.
  • Built upon a prototype application and user requirements.

Related Experiment Videos

Main Results:

  • A flexible system architecture for distributed collaborative radiological visualization was designed.
  • The system integrates modern hardware and established web/grid standards.
  • User requirements and system constraints were evaluated.

Conclusions:

  • The designed system provides a flexible foundation for distributed collaborative radiological visualization.
  • The approach effectively combines hardware advancements with standard technologies.
  • Further evaluation of system constraints ensures practical applicability.