Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

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

The Effect of Stirrup Length on Impact Attenuation and Its Association With Muscle Strength.

Journal of strength and conditioning research·2020

Same author

High-Resolution Structure of ClpC1-Rufomycin and Ligand Binding Studies Provide a Framework to Design and Optimize Anti-Tuberculosis Leads.

ACS infectious diseases·2019

Same author

Rufomycin Targets ClpC1 Proteolysis in Mycobacterium tuberculosis and M. abscessus.

Antimicrobial agents and chemotherapy·2019

Same author

Kinetic Analysis of Isometric Back Squats and Isometric Belt Squats.

Journal of strength and conditioning research·2018

Same author

VISUAL FEEDBACK ARRAY TO ACHIEVE REPRODUCIBLE LIMB DISPLACEMENTS AND VELOCITIES IN HUMANS.

Biomedical sciences instrumentation·2018

Same author

Metabolite Profiling and Classification of DNA-Authenticated Licorice Botanicals.

Journal of natural products·2015

Search research articles

Related Experiment Video

Updated: Jun 24, 2026

Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging

Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging

Published on: July 11, 2025

Graphical user interface to optimize image contrast parameters used in object segmentation - biomed 2009.

Jeffrey R Anderson¹, Steven F Barrett

¹University of Wyoming, Laramie, WY.

Biomedical Sciences Instrumentation

|April 17, 2009

Summary

This study introduces a graphical user interface (GUI) to enhance image segmentation by allowing users to adjust contrast. The GUI improves object recognition in medical images like MRI and CLSM, aiding 3D visualization.

More Related Videos

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

Substructure Analyzer: A User-Friendly Workflow for Rapid Exploration and Accurate Analysis of Cellular Bodies in Fluorescence Microscopy Images

Substructure Analyzer: A User-Friendly Workflow for Rapid Exploration and Accurate Analysis of Cellular Bodies in Fluorescence Microscopy Images

Published on: July 15, 2020

Related Experiment Videos

Last Updated: Jun 24, 2026

Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging

Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging

Published on: July 11, 2025

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

Substructure Analyzer: A User-Friendly Workflow for Rapid Exploration and Accurate Analysis of Cellular Bodies in Fluorescence Microscopy Images

Substructure Analyzer: A User-Friendly Workflow for Rapid Exploration and Accurate Analysis of Cellular Bodies in Fluorescence Microscopy Images

Published on: July 15, 2020

Area of Science:

Computer Vision
Medical Imaging
Image Processing

Background:

Image segmentation isolates objects but fully autonomous algorithms are lacking.
User-interactive methods improve segmentation for medical images (MRI, CLSM), aiding 3D visualization.
Optimal image contrast is crucial for effective segmentation and edge detection.

Purpose of the Study:

To develop a graphical user interface (GUI) for optimizing image contrast.
To enhance the performance of object segmentation algorithms through user-guided contrast adjustment.
To leverage human visual perception for improved image analysis.

Main Methods:

Developed a GUI enabling users to define grayscale ranges for histogram stretching.
Implemented interactive gamma correction for non-linear grayscale adjustments.
Integrated user-defined parameters to optimize contrast for segmentation.

Main Results:

The GUI facilitates intuitive contrast enhancement for improved image segmentation.
User interaction allows for optimal selection of contrast parameters.
Enhanced contrast leads to better object isolation in segmented images.

Conclusions:

The developed GUI effectively improves image segmentation by enabling user-driven contrast optimization.
Interactive contrast adjustment, guided by human perception, enhances segmentation accuracy.
This approach offers a powerful tool for visualizing complex structures in medical and scientific imaging.