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A counting method for density packed cells based on sliding band filter image enhancement

Cell loss and addition is an important biological event in pathology, and it usually provides central information to the changes of biological activity in the histological sections. To develop a reliable and accurate cell counting tools in tissue section, in this paper, we proposed a novel cell nuclei detecting method based on the sliding band filter which is a member of convergence index family. We evaluated the accuracy and performance of our method on density packed retinal outer nuclear layer cell confocal multivariate fluorescence microscopy image datasets. The results show our proposed method exhibited an excellent performance with its accuracy compared with human manual counting. It is worth noting that the proposed cell counting method can clearly benefit for retinal detachment and reattachment visual diagnostics close related to cell loss and addition.