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

FAME--a flexible appearance modeling environment.

Mikkel B Stegmann1, Bjarne K Ersbøll, Rasmus Larsen

  • 1Informatics and Mathematical Modelling, Technical University of Denmark, Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby, Denmark. mbs@imm.dtu.dk

IEEE Transactions on Medical Imaging
|October 14, 2003
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

Quark Mass Dependence of Heavy Quark Diffusion Coefficient from Lattice QCD.

Physical review letters·2024
Same author

High-Entropy Oxides in the Mullite-Type Structure.

Chemistry of materials : a publication of the American Chemical Society·2023
Same author

Heavy Quark Diffusion from 2+1 Flavor Lattice QCD with 320 MeV Pion Mass.

Physical review letters·2023
Same author

Multimodal soft tissue markers for bridging high-resolution diagnostic imaging with therapeutic intervention.

Science advances·2020
Same author

Prediction of pork quality parameters by applying fractals and data mining on MRI.

Food research international (Ottawa, Ont.)·2017
Same author

Metabolic Adaptation Establishes Disease Tolerance to Sepsis.

Cell·2017

This study introduces the Flexible Appearance Modeling Environment (FAME), a public domain tool for active appearance models (AAMs) in medical image analysis. FAME enhances image interpretation through robust shape and pixel intensity modeling, applicable to interactive medical applications.

Area of Science:

  • Medical Image Analysis
  • Computer Vision
  • Biomedical Engineering

Background:

  • Active Appearance Models (AAMs) offer robust image interpretation by combining pixel intensities and shape.
  • AAMs have broad applicability in various medical image analysis tasks.
  • Existing AAM implementations may lack accessibility or specific features for medical applications.

Purpose of the Study:

  • To summarize the applications of AAMs in medicine.
  • To introduce and describe a public domain implementation of AAMs called the Flexible Appearance Modeling Environment (FAME).
  • To provide guidelines for using FAME and demonstrate its applicability to interactive medical applications.

Main Methods:

  • Combined modeling of pixel intensities and shape using the AAM framework.

Related Experiment Videos

  • Development and description of the Flexible Appearance Modeling Environment (FAME) software.
  • Application of parallel analysis for automatic and objective model truncation to enhance performance and generalization.
  • Comparison of two AAM training methods.
  • Case study using cross-sectional short-axis cardiac magnetic resonance images and face images.

    • Main Results:

    • FAME provides a robust and widely applicable framework for medical image analysis.
    • Optimization techniques within FAME enable interactive medical applications.
    • Parallel analysis effectively improves model performance and generalization through automatic truncation.
    • Comparative analysis of training methods and validation on cardiac and facial imaging data.

    Conclusions:

    • The Flexible Appearance Modeling Environment (FAME) is a valuable, publicly available resource for advancing medical image analysis using Active Appearance Models.
    • FAME's design supports interactive applications and improved model generalization.
    • The study provides a reproducible research platform with source code and annotated datasets for further investigation in medical imaging.