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

Pressure-induced softening of locust bean gum hydrogels: A counterintuitive alternative to freeze-thaw stiffening.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Impact of Concurrent Graft-versus-Host Disease on Long-Term Survival in Critically Ill Patients Following Allogeneic Hematopoietic Stem Cell Transplantation for Hematological Malignancies.

Transplantation and cellular therapy·2026
Same author

Enhancing minority class recovery in high resolution land cover mapping with dynamic imbalance aware oversampling.

Scientific reports·2026
Same author

Haploidentical allogeneic haematopoietic stem cell transplantation for paroxysmal nocturnal haemoglobinuria: a retrospective analysis.

Annals of hematology·2026
Same author

Association of <i>katG</i>, <i>inhA,</i> and <i>AhpC</i> Mutations with Isoniazid Resistance of <i>Mycobacterium tuberculosis</i> in Pulmonary Tuberculosis Patients from Nanjing, China.

Microbial drug resistance (Larchmont, N.Y.)·2026
Same author

Empiric Imipenem/Cilastatin/Relebactam for Febrile Neutropenia After Allogeneic Hematopoietic Stem Cell Transplantation: Two Case Reports.

Journal of blood medicine·2026

Related Experiment Video

Updated: Mar 9, 2026

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

900

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines.

George Teodoro1,2, Tahsin M Kurç2,3, Luís F R Taveira1

  • 1Department of Computer Science, University of Brasília, Brasília 70910-900, Brazil.

Bioinformatics (Oxford, England)
|January 8, 2017
PubMed
Summary

This study introduces an efficient framework for sensitivity analysis and parameter tuning in large-scale image analysis, significantly reducing computational costs and improving segmentation quality. The approach enables scalable studies on large datasets with minimal user interaction.

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

13.5K
A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment
10:39

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

2.8K

Related Experiment Videos

Last Updated: Mar 9, 2026

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

900
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

13.5K
A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment
10:39

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

2.8K

Area of Science:

  • Computational imaging
  • High-performance computing
  • Image analysis workflows

Background:

  • Sensitivity analysis and parameter tuning are computationally expensive in large-scale image analysis.
  • Current methods require numerous workflow executions, hindering scalability for large datasets.

Purpose of the Study:

  • To develop an integrated solution for efficient sensitivity analysis and parameter tuning in image analysis.
  • To minimize user interaction and leverage high-performance computing for large-scale studies.

Main Methods:

  • Implementation of a novel framework integrating effective methodologies and high-performance computing.
  • Application to image segmentation workflows for parameter space exploration.

Main Results:

  • The approach rapidly identifies non-influential parameters, pruning the search space.
  • Improved segmentation quality (Dice and Jaccard metrics) by up to 1.42× compared to default parameters, using a small fraction of the parameter space.
  • Demonstrated scalability on high-performance computing clusters.

Conclusions:

  • The framework enables feasible sensitivity analyses, parameter studies, and auto-tuning on large datasets.
  • Facilitates quantification of error estimations and output variations in image segmentation pipelines.