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Measuring cellular migration with image processing


Migration of vascular endothelial cells is an important step in numerous physiological and pathological processes such as wound-healing and vascularisation of tumours. The mechanisms of cellular migration

need to be understood in order to develop therapies for a number of conditions and this requires suitable model systems. A simple and inexpensive method to study cell migration in vitro is with the scratch wound assay which consists of making an artificial wound in a monolayer of cells where is made by dragging a sterile sharp object such as a needle or micropipette through the cells or through electroporation with an electrical current. Yet, despite the wide use of these scratch wound assays, most of the analyses are limited to the visual observation of a series of micrographs, measurements are generally performed manually, and in the few cases where image processing is used, it requires the images to have a high density of cells, well defined borders, vertically-oriented straight boundaries, or a second fluorescent image.

An image-processing algorithm for the analysis of migration of vascular endothelial cells in culture is presented. The algorithm correctly detected the cellular regions on either side of an artificial wound made by dragging a sterile pipette tip across the monolayer of cells (scratch wound assay). Frequency filtering and mathematical morphology were used to approximate the boundaries of cellular regions. This allowed the measurement of the distance between the regions, and therefore the migration rates, regardless of the orientation of the wound and even in cases where the cells were sparse and not tightly packed.

This algorithm was published in Electronics Letters.

Together with other algorithms, CD31 stained images can be automatically processed through the CAncer IMage ANalysis website (CAIMAN).

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