1. A computer-aided pathological diagnosis method for the classification of cancer cells in a tissue specimen based on a digital cellular image of the tissue specimen, the method comprising the steps of: extracting the histological characteristic features of the cellular image using preprocessing algorithms having adaptive strategies to enhance the cellular image; declustering the cellular image to isolate the individual cells and the nuclei inside the cells using a distance-transform that yields the minimal distance to the boundary of an object for every pixel in the cellular image, wherein the distance-transform is given by Y ⁡ ( x , y ) = { min ⁢   ( x , y ) - η ⁡ ( x k , y k )   Vk } , where the coordinate of every pixel x=(x;y) in a uniform area (x;y)ε A and η(x k ;y k ) is the surrounding curve of the area; segmenting the declustered cellular image; labeling the segmented cellular image; and classifying the cells in the labeled cellular image as cancer cells or non-cancer cells.