Trinion Based Wbc Segmentation Using Texture To Detect Acute Lymphoblastic Leukemia

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Many diseases are detected based on examination of microscopic images of blood samples.rnChanges in the blood condition show the development of diseases in an individual. One type ofrndisease caused by change of blood condition is Leukemia. Leukemia can cause early death whenrnit is not treated on time. In Ethiopia, Leukemia accounts to about 35.5% of hematologicalrnadmissions. The death rate in Ethiopia due to Leukemia is different with time and region. Thernaverage death rate is increasing from time to time and shows variation between country side andrnurban population. Reports from the World Health Organization (WHO) show that death rate duernto Leukemia in Ethiopia has reached 5.56% and ranked 18rnthrn highest in the world.rnLeukemia originates in the bone marrow, a thin material inside the bone. Leukemia is detected rnby analyzing white blood cells (WBCs also called Leucocytes), one of the constituents of bloodrnalong with red blood cells (RBC or Erythrocytes), platelets and blood plasma. WBCs have fiverndifferent types (Lymphocytes, Myelocytes, Neutrophils, Basophils and Eosinophils) and amongrnthese Lymphocytes and Myelocytes are the ones that could start to change in the bone marrowrnand get infected and become Leukemic or infected cells. These Leukemia cells have strangernproperties compared to the normal cells in that their growth is abnormal and they survive muchrnlonger than the normal cells. They also interrupt functions of the normal cells. Through time, thernnormal cells perish while leukemia cells still survive. Old leukemia cells last for a longer timernand production of new leukemia continue in an abnormal way. rnTraditionally, Leukemia detection is carried out manually based on visual examination ofrnmicroscopic images of blood samples. This is lengthy and time taking process which depends onrnthe skills and experiences of the observer which makes the process subjective. In this regard,rncomputer based automated schemes play their great role and several efforts have been made inrnthe literature to develop such schemes. rnIn the current study, a novel mathematical technique for Leukemia detection based on holisticrnanalysis of color microscopic images of blood samples is proposed. The approach utilizes arnholistic representation of microscopic blood images in the three (Trinion) space and appliesrntrinion based Fourier transform implemented in the L*a*b color space to extract useful higherrnorder features to segment normal and infected WBCs and classify them. The technique has beenrnapplied in analyzing microscopic images acquired from standard ALL-IDB database.rnClassification of normal and Leukemic WBCs was performed based of Artificial Neural Networkrn(ANN) which resulted in 95.7% sensitivity, 100% specificity and 97.6% accuracy.

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Trinion Based Wbc Segmentation Using Texture To Detect Acute Lymphoblastic Leukemia

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