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

An architecture for implementing customizable medical image processing systems.

A M Demiris1, C E Cardenas, M H Makabe

  • 1Deutsches Krebsforschungszentrum, Div. 0805 Medical and Biological Informatics, Heidelberg, Germany. A.M.Demiris@dkfz-heidelberg.de

Studies in Health Technology and Informatics
|June 29, 1999
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

iPad-assisted percutaneous nephrolithotomy (PCNL): a matched pair analysis compared to standard PCNL.

World journal of urology·2019
Same author

Medical Images in Integrated Health Care Workstations.

Yearbook of medical informatics·2016
Same author

Image and Signal Processing.

Yearbook of medical informatics·2016
Same author

Erratum to: OpenHELP (Heidelberg laparoscopy phantom): development of an open-source surgical evaluation and training tool.

Surgical endoscopy·2015
Same author

OpenHELP (Heidelberg laparoscopy phantom): development of an open-source surgical evaluation and training tool.

Surgical endoscopy·2015
Same author

Magnetic tracking in the operation room using the da Vinci(®) telemanipulator is feasible.

Journal of robotic surgery·2013
Same journal

A GenAI Pipeline for Violinist Kinematic Data Management.

Studies in health technology and informatics·2026
Same journal

AMAL-For-Qatar: A Comprehensive AI Ecosystem for Fetal Ultrasound Analysis - Project Overview and Achievements.

Studies in health technology and informatics·2026
Same journal

Longitudinal Treatment-Aware Multimodal AI for Dermatology: A Scoping Review.

Studies in health technology and informatics·2026
Same journal

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026
Same journal

Validation of Deep-Learning Models for Autosegmentation of Brain Metastases.

Studies in health technology and informatics·2026
Same journal

Delay-Dependent Gating in Modular RNNs.

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

Monolithic medical image processing systems are complex. This work introduces a customizable architecture for intuitive, adaptable medical imaging systems, easing the workload for medical personnel.

Area of Science:

  • Medical Imaging
  • Computer Science
  • Human-Computer Interaction

Background:

  • Monolithic medical image processing systems are often difficult to use, requiring specialized knowledge and increasing medical personnel workload.
  • Existing systems lack flexibility, hindering adaptation to diverse medical imaging challenges.

Purpose of the Study:

  • To present an architecture for creating customizable medical image processing systems.
  • To simplify the use and adaptation of medical imaging software for healthcare professionals.

Main Methods:

  • Developed a generalized algorithm model and repository for goal-oriented system customization.
  • Implemented dynamic, data-oriented parameterization for selected algorithms.
  • Enabled semi-automated generation of user interface components based on cognitive ergonomics.

Related Experiment Videos

Main Results:

  • An object-oriented framework was created for building customizable medical imaging system components.
  • The architecture facilitates easier integration and adaptation of imaging functionalities.

Conclusions:

  • The proposed architecture enables the development of user-friendly and adaptable medical image processing systems.
  • This approach enhances efficiency and reduces the burden on medical personnel by providing tailored imaging solutions.