This paper presents an efficient and innovative method for the automated counting of cells in a microscopic image. The performance of watershed-based algorithms for the segmentation of clustered cells has been well demonstrated. The strength of our algorithm lies in the fact that it incorporates knowledge of color in the image. Our method uses the watershed transform with iterative shape alignment and is shown to be more accurate in retaining cell shape. We report a sensitivity of 97% and specificity of 96% when all color bands are used. Our methods could be of value to computer-based systems designed to objectively interpret microscopic images, since they provide a means for accurate cell segmentation.
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