Detection of the Leukemia Disease

Abstract

Leukemia develops when the DNA of a single cell in your bone marrow alters (mutates), causing it to be unable to develop and function normally. Leukemia cells frequently act similarly to aberrant white blood cells. Hematologists employ microscopic analysis of human blood, which necessitates the use of technologies such as microscopic color imaging, segmentation, classification, and clustering to identify individuals with leukemia. The microscopic images are visually analyzed by hematologists, which is a time-consuming and laborious approach. The automatic image processing system is desperately needed and can help overcome visual inspection limits. The proposed system that we have suggested will use microscopic images to diagnose leukemia. The capacity to detect leukemia early and efficiently aids in the development of its appropriate treatment. Statistical measures such as mean and standard deviation are used to identify white blood cells from other blood components such as erythrocytes and platelets. For leukemia diagnostic prediction, geometrical characteristics of the white blood cell nucleus, such as area and perimeter, are investigated. The suggested approach has been applied to a large number of photos with promising results for images of different quality. ALL (Acute lymphoblastic leukemia) is a cancer that affects the lymphoid progenitor cells present in the bone marrow, blood, and extracellular locations. Even though 80% of ALL cases are in children, it is a severe disease in adults. In the United States, ALL is projected to affect 1.6 persons out of every 100,000 people. Approximately 1400 persons died from ALL in 2016, with an estimated 6590 new cases as per American Cancer Society. ALL has a bimodal incidence, with its first peak occurring in the childhood and the second peak occurring at 50 years old. While dose-intensification techniques have improved outcomes for children, the elderly continue to have a bad prognosis.