CSMA: A Standalone and ImageJ-Compatible Tool for Enhanced Wound Healing Assay Analysis

Accurate quantification of wound closure in cell migration assays is crucial yet challenging. Still, existing methods often underperform due to omitting cell detection within the wound area, resulting in biased outcomes. We developed the CSMA standalone and ImageJ-compatible tool, which utilizes adv...

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Main Authors: Tri Thanh Pham, Amina Sagymbayeva, Timur Elebessov, Zhadyra Onzhanova, Ferdinand Molnar
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10966915/
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author Tri Thanh Pham
Amina Sagymbayeva
Timur Elebessov
Zhadyra Onzhanova
Ferdinand Molnar
author_facet Tri Thanh Pham
Amina Sagymbayeva
Timur Elebessov
Zhadyra Onzhanova
Ferdinand Molnar
author_sort Tri Thanh Pham
collection DOAJ
description Accurate quantification of wound closure in cell migration assays is crucial yet challenging. Still, existing methods often underperform due to omitting cell detection within the wound area, resulting in biased outcomes. We developed the CSMA standalone and ImageJ-compatible tool, which utilizes advanced image processing techniques, including contrast enhancement, edge detection, and morphological operations, to precisely identify and quantify cells in the wound region. CSMA offers user-friendly features and adjustable parameters to accommodate different imaging conditions, ensuring robust performance across diverse experimental setups. Validation against conventional tools confirms CSMA&#x2019;s superior ability to delineate wound boundaries and provide accurate estimations of area and width at every time point. As applied to SW480-ADH colon cancer cells treated with various compounds, CSMA proves valuable in biomedical research. CSMA represents a significant advancement in wound healing assay analysis, providing researchers with a simple and reliable tool for studying cell migration dynamics with enhanced precision and reproducibility. CSMA is available as a standalone and ImageJ-compatible tool with its source code at <uri>https://github.com/AminaSagymbayeva/CSMA_WoundHealing</uri>
format Article
id doaj-art-def9bb3fbb7e492fbc8893938b36d1a0
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issn 2169-3536
language English
publishDate 2025-01-01
publisher IEEE
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series IEEE Access
spelling doaj-art-def9bb3fbb7e492fbc8893938b36d1a02025-08-20T02:18:58ZengIEEEIEEE Access2169-35362025-01-0113693416935210.1109/ACCESS.2025.356160710966915CSMA: A Standalone and ImageJ-Compatible Tool for Enhanced Wound Healing Assay AnalysisTri Thanh Pham0https://orcid.org/0000-0003-1026-2146Amina Sagymbayeva1https://orcid.org/0009-0004-8478-8137Timur Elebessov2https://orcid.org/0009-0005-8998-9226Zhadyra Onzhanova3https://orcid.org/0009-0001-9304-9027Ferdinand Molnar4https://orcid.org/0000-0001-9008-4233Laboratory of Mechanobiology, Nazarbayev University, Astana, KazakhstanLaboratory of Mechanobiology, Nazarbayev University, Astana, KazakhstanLaboratory of Mechanobiology, Nazarbayev University, Astana, KazakhstanDepartment of Biology, School of Sciences and Humanities, Laboratory of Cell Growth Regulation, Nazarbayev University, Astana, KazakhstanDepartment of Biology, School of Sciences and Humanities, Laboratory of Cell Growth Regulation, Nazarbayev University, Astana, KazakhstanAccurate quantification of wound closure in cell migration assays is crucial yet challenging. Still, existing methods often underperform due to omitting cell detection within the wound area, resulting in biased outcomes. We developed the CSMA standalone and ImageJ-compatible tool, which utilizes advanced image processing techniques, including contrast enhancement, edge detection, and morphological operations, to precisely identify and quantify cells in the wound region. CSMA offers user-friendly features and adjustable parameters to accommodate different imaging conditions, ensuring robust performance across diverse experimental setups. Validation against conventional tools confirms CSMA&#x2019;s superior ability to delineate wound boundaries and provide accurate estimations of area and width at every time point. As applied to SW480-ADH colon cancer cells treated with various compounds, CSMA proves valuable in biomedical research. CSMA represents a significant advancement in wound healing assay analysis, providing researchers with a simple and reliable tool for studying cell migration dynamics with enhanced precision and reproducibility. CSMA is available as a standalone and ImageJ-compatible tool with its source code at <uri>https://github.com/AminaSagymbayeva/CSMA_WoundHealing</uri>https://ieeexplore.ieee.org/document/10966915/Cell migrationwound healingscratch assayanalysis tooladvanced image processingImageJ integration
spellingShingle Tri Thanh Pham
Amina Sagymbayeva
Timur Elebessov
Zhadyra Onzhanova
Ferdinand Molnar
CSMA: A Standalone and ImageJ-Compatible Tool for Enhanced Wound Healing Assay Analysis
IEEE Access
Cell migration
wound healing
scratch assay
analysis tool
advanced image processing
ImageJ integration
title CSMA: A Standalone and ImageJ-Compatible Tool for Enhanced Wound Healing Assay Analysis
title_full CSMA: A Standalone and ImageJ-Compatible Tool for Enhanced Wound Healing Assay Analysis
title_fullStr CSMA: A Standalone and ImageJ-Compatible Tool for Enhanced Wound Healing Assay Analysis
title_full_unstemmed CSMA: A Standalone and ImageJ-Compatible Tool for Enhanced Wound Healing Assay Analysis
title_short CSMA: A Standalone and ImageJ-Compatible Tool for Enhanced Wound Healing Assay Analysis
title_sort csma a standalone and imagej compatible tool for enhanced wound healing assay analysis
topic Cell migration
wound healing
scratch assay
analysis tool
advanced image processing
ImageJ integration
url https://ieeexplore.ieee.org/document/10966915/
work_keys_str_mv AT trithanhpham csmaastandaloneandimagejcompatibletoolforenhancedwoundhealingassayanalysis
AT aminasagymbayeva csmaastandaloneandimagejcompatibletoolforenhancedwoundhealingassayanalysis
AT timurelebessov csmaastandaloneandimagejcompatibletoolforenhancedwoundhealingassayanalysis
AT zhadyraonzhanova csmaastandaloneandimagejcompatibletoolforenhancedwoundhealingassayanalysis
AT ferdinandmolnar csmaastandaloneandimagejcompatibletoolforenhancedwoundhealingassayanalysis