Colour based Image Segmentation for Automated Detection of Leukaemia: A comparison between CIELAB and CMYK colour spaces

Leukaemia is an abnormal proliferation of White Blood Cells in the bone marrow and peripheral blood. The diagnosis of leukaemia is done by the pathologists and haematologists by observing a peripheral blood smear and bone marrow smear under a microscope. Advanced cytochemistry tests, immunophenotyping, flow cytometry, chromosome analysis etc. are used to confirm the incidence of leukaemia. Since these tests are time intense and exorbitant, image analysis of the blood and bone marrow smear can be used to assist the pathologists and haematologists for a quick diagnosis of leukaemia. A simple method to detect the incidence of leukaemia automatically by image processing techniques is proposed in this paper. The method uses colour based image segmentation using k-means clustering and image analysis by Hausdorff Dimension to detect leukaemia. The image in the RGB colour model is converted to the CIELAB as well as CMYK colour spaces and a comparison between the two in detecting leukaemia is also presented.