Abstrato

Automated diagnosis of acute lymphocytic leukemia and acute myeloid leukemia using multi-SV.

Saravana Kumar P

Leukemia is a blood cancer which is curable one in the early period, especially among children, adults and even for old people too. Most treatments comprise chemotherapy, therapeutic radioactivity therapy, or hormone dealings. The pace of remedy be contingent on the type of Leukemia as well as the age of victims. An early stage of Leukemia can be diagnosed and alleviated by proficient pathologist in patients. Despite a pathologist will also find some difficulty in recognizing and making for positive affirmation in detection of type of Leukemia after analysing the biological features of microscopic image of blasted cell. Therefore, the automated classification system for Leukemia detection is being the need of the hour in order to consume the time in diagnosing. Acute lymphocytic Leukemia, Acute myeloid Leukemia and normal cases of Microscopic images of blood marrow smears initially extracted the nucleus by removing background using segmentation. Then the blasted nuclei’s colour, GLCM and geometric features are extracted and finally these cells are classified as cancerous or non-cancerous cell and its subtypes using multi-support vector machine (SVM) classifier. The accuracy of the classifier evaluated up to 90%. The experimental results shows that proposed algorithm could attain an adequate performance for the diagnosis of AML, ALL and their sub-types.