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 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>
Authors
- Ferdinand Molnár (ORCID: https://orcid.org/0000-0001-9008-4233)
- Tri Thanh Pham (ORCID: https://orcid.org/0000-0003-1026-2146)
- Zhadyra Onzhanova
- Timur Elebessov (ORCID: https://orcid.org/0009-0005-8998-9226)
- Amina Sagymbayeva
Institutions
- Nazarbayev University (KZ)
Publication Details
- Journal
- IEEE Access
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/access.2025.3561607
- Primary Topic
- Cell Image Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00