Detection of Leukemia in blood Samples using Microscopic Images

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The book explores a preliminary study on detecting various types of leukemia through the analysis of microscopic blood sample images. It emphasizes the importance of early disease detection, allowing for timely intervention and prevention. By utilizing cost-effective imaging techniques, the study focuses on the characteristics of white blood cells, examining changes in texture, geometry, color, and statistical features as classifiers. It also reviews existing literature and proposes the use of Reinforcement Learning for leukemia classification, addressing relevant research challenges.