A Robust Morphological Approach for Automated Segmentation and Quantification of Scratch Assay Micrographs

Aykut Erdamar; Tansel Uyar

doi:10.5566/ias.3993

Authors

Dr. Aykut Erdamar Başkent Universtiy
Dr. Tansel Uyar Department of Biomedical Engineering, Faculty of Engineering, Başkent University, Ankara, Turkey.

DOI:

https://doi.org/10.5566/ias.3993

Keywords:

Cell migration, Image analysis, Imaging techniques, Scratch assay, Wound healing

Abstract

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.

Author Biographies

Dr. Aykut Erdamar, Başkent Universtiy

Dr. Aykut Erdamar, is a Professor (Associate) in the Department of Biomedical Engineering at Başkent Üniversity. His research interests include biomedical signal and image processing, deep learning architectures, and physiological signal analysis
Dr. Tansel Uyar, Department of Biomedical Engineering, Faculty of Engineering, Başkent University, Ankara, Turkey.

Dr. Tansel Uyar, is an Assist.Professor in the Department of Biomedical Engineering at Başkent University. His research interests include biomedical image processing and deep learning architectures.

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