PAPERZILLA
Crunching Academic Papers into Bite-sized Insights.
About
Sign Out
← Back to papers
Health Sciences › Medicine › Rehabilitation
An image J plugin for the high throughput image analysis of in vitro scratch wound healing assays
★
★
★
☆
☆
SHARE
Overview
Paper Summary
Conflicts of Interest
Identified Weaknesses
Rating Explanation
Good to know
Topic Hierarchy
File Information
Paper Summary
Paperzilla title
Automating Scratch Assays: A New Plugin for ImageJ (But Is It Really That Good?)
This paper introduces a new ImageJ/Fiji plugin, 'Wound Healing Size Tool', for analyzing in vitro scratch wound healing assays. This plugin aims to automate the process of quantifying wound area, coverage, average width, and width standard deviation, allowing for high-throughput analysis of scratch assays. Testing shows that conditioned media from hAdMSCs promotes faster wound closure and higher cell migration rates in HaCaT cells compared to control media.
Possible Conflicts of Interest
Funding was provided by the Department of Biomedical Engineering at Universidad de los Andes and by the start-up funding to Assistant Professors FAPA of Carolina Muñoz. Additionally, funding was provided by an internal call for termination of publications from the Vice-provost of Research at Universidad de los Andes. Although declared as not competing, these internal funding sources might exert some implicit bias.
Identified Weaknesses
Parameter Sensitivity
The plugin's performance is highly dependent on user-defined parameters, making it prone to inaccuracies if not set correctly. This dependence reduces the tool's reliability and introduces user bias.
Limited Generalizability
The evaluation of the plugin is limited to a small sample size and specific cell type. More diverse biological models and larger datasets should be used to validate its broader applicability.
Marginal Accuracy Improvement
Comparison with existing manual and other software methods reveals that the plugin may not offer significant advantages in terms of accuracy. The plugin showed comparable results to MiToBo, while manual and the other software method overestimated area values. This calls into question the added value of the proposed plugin over existing solutions.
Not Truly Automated
While the plugin aims to automate the image analysis process, its parameterization requires a preliminary manual step. This user input diminishes the fully automated aspect that the plugin aims to deliver.
Rating Explanation
This study presents a novel ImageJ plugin for automated analysis of scratch wound healing assays. While the tool offers some automation, it suffers from parameter sensitivity and does not significantly improve accuracy over existing methods, limiting its overall impact. The internal funding sources and potential bias also influence the rating.
Good to know
This is our free standard analysis. Paperzilla Pro fact-checks every citation, researches author backgrounds and funding sources, and uses advanced AI reasoning for more thorough insights.
Explore Pro →
Topic Hierarchy
File Information
Original Title:
An image J plugin for the high throughput image analysis of in vitro scratch wound healing assays
File Name:
file.pdf
[download]
File Size:
2.42 MB
Uploaded:
July 14, 2025 at 10:56 AM
Privacy:
🌐 Public
© 2025 Paperzilla. All rights reserved.