The tissue-like P Systems, which are 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 to identify various details and objects in those images. It is a highly challenging process, especially when dealing with blood smear images, which have a very complex cell structure. In order to analyze each object individually and to avoid the cumbersome and error-prone existing manual methods, images can be segmented using appropriate automated segmentation techniques. The proposed work aims at segmenting the nuclei of the White Blood Cells (WBCs) of the peripheral blood smear images, using tissue-like P Systems, 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.
Abstract. Mango plants are generally affected by various pests. The stem borer is a very harmful pest as its grub feeds on the internal parts of the tree leaving very little external evidence of damage to the host plant. Existing pest management methods suffer from the lack of knowledge about the precise location of the pest within the plant and the extent of internal damage. Recent laboratory experiments prove that these drawbacks can be overcome by using radiography as a means of study of the internal constituents of the plant's stem. This paper proposes a method to precisely segment the tree trunk followed by the segmentation of the stem boring insect's tunnels that appear in an X-ray image.
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