Automatic scene comparison and matching in multimodal cytopathological microscopic images

The potential of cytopathologic diagnoses to detect cancer of a variety of types non-invasively, cost-efficiently and up to three years ahead of conventional histopathologic diagnoses can be increased by the application of adjuvant methods, i.e. the combination of different stainings. For further improvement of cytopathology we introduced multimodal cell analysis (MMCA) which combines specific information about identical cells in different stainings successively applied to the same microscope slide. This requires a precise relocation and coregistration of individual cells under scrutiny. As a precondition for application in daily routine and screening settings the crucial relocation of cells has to be automated. The paper describes a method for an automatic retrieval of images of cells which have already been selected and recorded in a preceding staining together with their coordinates. Due to inevitable mechanical inaccuracies the geometric match is insufficient. The comparison of nuclear constellations based on segmentations in both stains facilitates an automatic correction of the position even if there is a subscene matching only. The process furthermore generates the initial guess for the succeeding coregistration which thereby gains robustness. The success rate of the method described is about 85%.