Computer analysis of histopathological images for tumor grading

OBJECTIVE

We developed a new method that enables automatic and rapid assessment of a tumor's proliferation index from immunohistochemically (IHC) stained microscopic images.

APPROACH

The method is based on computer-aided analysis of images - color filtration pixel-by-pixel (CFPP method) of the whole histopathological virtual slides.

MAIN RESULTS

The method is simple, rapid, and does not require the time consuming step of selecting manually areas of interest nor the need for computationally complicated detection of hot-spots, both of which attempt to emulate a pathologist's way of estimating a proliferation index. We apply our method to a set of diffuse large B-cell lymphoma (DLBCL) slide images.

SIGNIFICANCE

By appropriate changes in the color filtration thresholds, our method may be adapted to the analysis of other types of tumors. It may also be adapted for analysis of microscopic images in neuropathology, like biopsies of dystrophic muscles. Because of its simplicity and rapidity it may also be applied for analysis of series of images to assess dynamics of image complexity in network physiology.