Segmentation of Peripheral Blood Smear Images Using Tissue-Like P Systems

Abstract

Segmentation of medical images is a highly challenging process, especially when dealing with blood smear images, which have a very complex cell structure. The tissue-like P Systems, actually based on the methodology of cell and tissue behavior in a human body, are used in various areas of computation. Segmentation of medical images is one such area where these systems can be used, whereby the various objects in the images can be identified. The proposed work aims at segmenting the nuclei of the White Blood Cells (WBCs) of the peripheral blood smear images, which can help to identify various pathological conditions. In the first approach, segmentation is color based. The second approach is intensity based. In the third approach, morphology is used to strengthen the findings from the results.