bioRxivBioinformaticsPreprint
CSMA: an ImageJ Plugin for the Analysis of Wound Healing Assays
Tri Thanh PhamiD, Amina SagymbayevaiD, Timur ElebessoviD, Zhadyra OnzhanovaiD, Ferdinand MolnáriD
Abstract
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. To overcome this limitation, we developed the CSMA plugin for ImageJ. CSMA utilizes advanced image processing techniques, including contrast enhancement, edge detection, and morphological operations, to precisely identify and quantify cells in the wound region. The plugin offers user-friendly features and adjustable parameters to accommodate different imaging conditions, ensuring robust performance across diverse experimental setups. Validation against conventional tools confirms CSMAs 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. It 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 an ImageJ plugin and source code at https://github.com/AminaSagymbayeva/CSMA_WoundHealing.
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