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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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| 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’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 |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| 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’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 |