Abstract
This paper proposes an automatic system for detecting WBC cancers like AML, ALL, CLL, and CML, integrating image processing techniques. By automating analysis through advanced algorithms, it eliminates operator variability, ensuring consistent and objective results. Machine learning models classify cells for high accuracy, and seamless healthcare integration. This approach promises to enhance diagnostic efficiency and reliability in WBC cancer detection. Key Words: Image processing; WBC cancer; Leukemia; CNN
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