Computer aided leukemia detection using digital image processing techniques

The machine-controlled identification of malignant cells from microscopic diagnostic assay pictures of blood samples helps in assuaging the diagnostic problems of leukemia and provides higher results if the biologically explainable and clinically important feature primarily based approaches are used for the identification of malignancy and the severity of the disease. Identification method might have error rates up to 40%; Due to this drawback it is necessary to develop a second opinion tool which helps the doctors and pathologists in a classified detection of the leukemia disease. The analysis shows a discourse method for leukemia and its subtypes detection from microscopic blood cell images which can be done by applying image processing techniques followed by a detailed classification analysis on the dataset images.