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 Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Management of severe acute alcoholic hepatitis in France: results of a national survey: R1.

Clinics and research in hepatology and gastroenterology·2026
Same author

Editorial: Chronic Hepatitis Delta-We Need More Screening to Improve Knowledge on the Natural History.

Alimentary pharmacology & therapeutics·2025
Same author

Knee extension strength in patients with liver cirrhosis and the impact of interventions: systematic review and meta-analysis.

Acta gastro-enterologica Belgica·2025
Same author

Advanced stage adenoid cystic carcinoma of the sinonasal cavity and skull base: a retrospective 20-year analysis.

International journal of oral and maxillofacial surgery·2024
Same author

Editorial: How often can we get the right diagnosis after bone marrow transplant in patients with abnormal liver function tests?

Alimentary pharmacology & therapeutics·2024
Same author

Water in the terrestrial planet-forming zone of the PDS 70 disk.

Nature·2023

Related Experiment Video

Updated: Apr 18, 2026

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
07:54

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence

Published on: October 25, 2011

19.3K

A feature selection based framework for histology image classification using global and local heterogeneity

J Coatelen, A Albouy-Kissi, B Albouy-Kissi

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 9, 2015
    PubMed
    Summary
    This summary is machine-generated.

    Objective histological image analysis improves chronic liver disease diagnosis. A new framework uses feature selection to identify key tissue descriptors, enhancing accuracy and reducing complexity for reliable liver fibrosis grading.

    More Related Videos

    Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging
    08:40

    Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

    Published on: April 8, 2016

    13.6K
    Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research
    05:22

    Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research

    Published on: June 21, 2024

    989

    Related Experiment Videos

    Last Updated: Apr 18, 2026

    Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
    07:54

    Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence

    Published on: October 25, 2011

    19.3K
    Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging
    08:40

    Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

    Published on: April 8, 2016

    13.6K
    Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research
    05:22

    Author Spotlight: Enhanced Multiplex Immunofluorescent Microscopy Protocol for Neuroscience Research

    Published on: June 21, 2024

    989

    Area of Science:

    • Digital pathology
    • Computational biology
    • Medical imaging analysis

    Background:

    • Liver biopsy is the standard for diagnosing chronic liver diseases.
    • Reader variability in histological analysis necessitates objective tissue description methods.
    • Current methods lack comprehensive, objective tissue analysis frameworks.

    Purpose of the Study:

    • To develop and validate a framework for objective histological image analysis.
    • To identify the most relevant subset of image descriptors for accurate classification.
    • To enable classification using combined global and local tissue measurements.

    Main Methods:

    • Implemented a framework for analyzing histological images from any tissue type.
    • Utilized a feature selection approach to identify key descriptors.
    • Computed relevant descriptor subsets from an initial list of 258 global and local descriptors.

    Main Results:

    • Achieved 82.8% accuracy in human liver fibrosis grading.
    • Selected a significantly shorter list of 6 descriptors for high accuracy.
    • Demonstrated classification using combinations of global and local measurements.

    Conclusions:

    • The developed framework provides an objective method for histological image analysis.
    • Feature selection effectively reduces descriptor numbers while maintaining classification accuracy.
    • This approach offers a more reliable and efficient tool for liver fibrosis grading.