A region extraction approach to blood smear segmentation

Abstract

A major problem in the development of systems for automated differential blood count of leucocytes of the peripheral blood is the correct segmentation of the cell scene. Standard preparation techniques of blood smears have been optimized for the visual inspection of the cell scene. Variations in the preparation have a negligible effect on the scene evaluation by visual analysis but do pose major problems on an automated analysis. Therefore a new algorithm for the segmentation of microscopic cell scenes of leucocytes has been developed which uses, in addition to local properties of the scene, global information about neighborhood relations and shape of the scene components for the improvement of the segmentation. The algorithm is based on a region extraction approach and a subsequent labeling procedure. A priori knowledge about shape and neighborhood relations is entered by a relaxation process.