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

XML knowledge database of MRI-derived eye models.

Holger Kunz1, Claus Derz, Thomas Tolxdorff

  • 1Institute of Medical Informatics, Biostatistics and Epidemiology, Benjamin Franklin Medical Center, Freie Universität Berlin, Hindenburgdamm 30, D-12200 Berlin, Germany.

Computer Methods and Programs in Biomedicine
|February 26, 2004
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

Automated Machine Learning Approaches for Surgery Duration Prediction in Orthopaedics.

Studies in health technology and informatics·2026
Same author

The Impact of Visual Feedback Design on Self-Regulation Performance and Learning in a Single-Session rt-fMRI Neurofeedback Study at 3T and 7T.

Brain sciences·2026
Same author

PRIMARY-AI: outcomes-based standards to safeguard primary care in the AI era.

Nature medicine·2026
Same author

The Implementation of Broad Consent at University Hospitals.

Deutsches Arzteblatt international·2025
Same author

On the relationship between viscoelasticity and water diffusion in soft biological tissues.

Acta biomaterialia·2024
Same author

Enhancing paranasal sinus disease detection with AutoML: efficient AI development and evaluation via magnetic resonance imaging.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery·2024
Same journal

SynTME: A tumor microenvironment-aware, pharmacology-inspired multi-stage framework for drug synergy prediction.

Computer methods and programs in biomedicine·2026
Same journal

MMFVS-Net: A triple-symmetric cross-attention network for multimodal optical image fusion and high-accuracy virtual staining of breast cancer tissues.

Computer methods and programs in biomedicine·2026
Same journal

A novel Milstein-stochastic epidemiologically-informed neural network for approaching epidemic dynamics: Application to Mpox disease.

Computer methods and programs in biomedicine·2026
Same journal

Accounting for approximation errors using surrogate-based parameter estimation of cardiac mechanics digital twins.

Computer methods and programs in biomedicine·2026
Same journal

Facial iPPG heatmap patterns based on period-aware autoencoder show association with carotid atherosclerosis towards non-contact hemodynamic assessment.

Computer methods and programs in biomedicine·2026
Same journal

Explainable machine learning models predict liver fibrosis risk and outcome in the general population: Development and multi-cohort external validation.

Computer methods and programs in biomedicine·2026
See all related articles

Researchers created a database of individual eye models using MRI scans. This system, built with XML and Java, successfully classifies and stores eye data, offering a transferable approach for similar classification tasks.

Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Computer Science

Background:

  • Accurate modeling of individual eye morphology is crucial for various ophthalmic applications.
  • Existing methods may lack efficient data storage and retrieval capabilities for complex eye features.

Purpose of the Study:

  • To develop a model-based approach for creating and managing a database of individual eye models.
  • To implement a structured, extensible, and Internet-accessible database for storing specific eye morphology features.

Main Methods:

  • Utilized Magnetic Resonance (MR) images to construct individual eye models.
  • Developed an Extensible Markup Language (XML) structure and Document Type Definition (DTD) for data management.
  • Implemented a classification and retrieval system in Java.

Related Experiment Videos

Main Results:

  • Successfully created a database storing individual eye models with specific morphological features.
  • The Java-based system effectively classified data sets.
  • Classified data were integrated into the database.

Conclusions:

  • The model-based approach provides an effective method for storing and classifying individual eye data.
  • The implemented XML structure and Java system are robust and extensible.
  • This methodology can be readily adapted for similar classification and database management applications.