Detection and Separation of Overlapping Cells Based on Contour Concavity for Leishmania images

Life scientists often must count cells in microscopy images, which is a tedious and time-consuming task. Automatic approaches present a solution to this problem. Several procedures have been devised for this task, but the majority suffer from performance degradation in the case of cell overlap. In this paper, we propose a method to determine the positions of macrophages and parasites in fluorescence images of Leishmania-infected macrophages. The proposed strategy is primarily based on blob detection, clustering and separation using concave regions of the cells' contours. In comparison with the approaches of Nogueira and Leal et al., which also addressed this type of image, we conclude that the proposed methodology achieves better performance in the automatic annotation of Leishmania infections.

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Some annotated images using our method:

Leishmania-infected macrophages imageExample 1 Leishmania-infected macrophages image Example 2 Leishmania-infected macrophages imageExample 3 Leishmania-infected macrophages image Example 4