Blood Cancer Detection with Microscopic Images Using Machine Learning

K-means transformation, histogram equalization, linear contrast stretching, and share-based features are all used to detect leukemia. A method for automatically classifying leukocytes using microscopic images is proposed. This proposed model MATLAB find leukemia cells in healthy blood cells, it requires no medical equipment or expert heavily relies on automation. technology can anemia, malaria, vitamin B12 deficiency, brain tumors. The correctly identifies WBCs leukoblasts refines the identification, thresholding, segmentation phases. improves WBC counting overall accuracy, which leads better shape feature extraction, critical this problem. New type of analysis must also be studied analyzed. Finding most discriminatory will provide best accuracy. Determining whether adjacent separated an image.