Diagnosis of Leukemia Using Digital Image Segmentation of Blood Cells

Abstract: The early identification of leukemia form in cancer patients can greatly increase the likelihood of recovery. Diagnostic methods that distinguish among the disease's many forms are either costly or do not exist. Amongst the existing diagnostic methods are immune- phenotype and cytogenetic abnormality, which require time to obtain results and are costly to perform due to their requirement of well equipped laboratories. Thus, there is a need for fast and cost-effective method that results in the identification of the different leukemia forms or types. Therefore, we propose the use of digital image morphological analysis of microscopic images of leukemic blood cells for the identification purpose. We present in this paper the first phase of an automated leukemia form identification system, which is the segmentation of infected cell images. The segmentation process provides two enhanced images for each blood cell; containing the cytoplasm and the nuclei regions. Unique features for each form of leukemia can then be extracted from the two images and used for identification.

Keywords: Cancer Diagnosis, Leukemia Type, Blood Cell, Image Segmentation, Morphological Analysis.