Image Analysis and Stereology · Published 2026-07-04 · DOI 10.5566/ias.3993
Aykut Erdamar, Tansel Uyar
A variety of methodologies are available for the study of cell migration in vitro which has major function in physiological and pathophysiological processes even in cancer metastasis. The in vitro scratch assay is widely utilized for cell migration analysis. The straightforward, simple, and inexpensive procedure is performed manually; demonstrated to exhibit a high degree of similarity to the in vivo migratory behavior of cells. The scratch area is approximated to a rectangle or averaged to a certain number of parallel distances, performed by the analyst. Being laborious and time-consuming, the visual evaluation process is contingent upon the researcher’s professional expertise, leading to subjective outcomes in the results. Furthermore, factors such as differing experimental setups, imaging equipment and brightness differences in the images can also lead to subjective outcomes. In order to circumvent inherent subjectivity, utilization of fully automatic software is proposed for the segmentation and quantification of scratch assay micrographs. The proposed software’s algorithm is founded upon the principles of morphological image processing and rank filtering, encompassing a series of image processing steps. The results demonstrate that the software generates reproducible outputs even though parameters of the image such as brightness and contrast change. The algorithm offers a novel perspective in this field and functions as a robust and user-friendly computational instrument for end users, thereby reducing the subjectivity of the results.
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Erdamar, A., Uyar, T. (2026). A Robust Morphological Approach for Automated Segmentation and Quantification of Scratch Assay Micrographs. Image Analysis and Stereology. https://doi.org/10.5566/ias.3993