Analysis & Classification of Acute Lymphoblastic Leukemia using KNN Algorithm

Abstract

The early Detection of leukemia in cancer patients can greatly increase the chances of recovery. The leukemia can be identified by specific tests such as Cytogenetics and Immunophenotyping and morphological cell classification made by hematologist observing blood & marrow microscope images. This Diagnostic methods are costly and time consuming. We propose the use of morphological analysis of microscopic images of leukemic blood cells for the identification purpose, the morphological analysis just requires an image not a blood sample and hence is suitable for low cost and remote diagnostic system . The proposed system firstly individuates in the blood image the leucocytes from the others blood cells, then it select the lymphocyte cells (the ones interested by acute leukemia), it evaluates morphological indexes from those cells and finally it classifies the presence of the leukemia. 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.