Detection and Classification of Blood Cancer using an Auto Encoder and a Regularised Extreme Learning Machine

Leukemia is by far the most common type of blood cancer in humans. The length of time it takes to recover from an illness is determines by how quickly it is recognized and treated. Leukemia develops when the bone marrow generates an abnormally large amount of white blood cells. Because images of human blood samples are studied under the microscope, hematologists use techniques such as microscopic color imaging, image segmentation, grouping, and classification to diagnose patients as quickly and precisely as possible. Microscopy can identify blood cancer in visible and immature white blood cells in a variety of methods. Early and correct diagnosis of leukemia is critical for clinicians to properly treat patients. Following the submission of the input image, Image processing in image