AUTOMATIC LEUKEMIA DETECTION IN HUMAN BLOOD SAMPLE BASED ON MICROSCOPIC IMAGES USING MACHINE LEARNING

Naufa N N; Dr. Sajith V

Volume : VIII, Issue : XII, December - 2019

AUTOMATIC LEUKEMIA DETECTION IN HUMAN BLOOD SAMPLE BASED ON MICROSCOPIC IMAGES USING MACHINE LEARNING

Naufa N N, Dr. Sajith V

Abstract :

One of the major diseases which causes death among human is leukemia. Cure rate depends mainly on the early detection as well as diagnosis of the disease. The proposed method is about the method of automatic leukemia detection. In manual method, experienced physician counts white blood cells (WBC) inorder to detect leukemia from the images taken from the microscope. But, this method is time consuming and not so accurate, because it completely depends upon the physician�s skill. Automatic technique of detecting leukemia is developed inorder to overcome these drawbacks.. These features are used as the classifier input. Image Processing, Segmentation, Fill hole operations, feature extraction and classification are done to obtain the cancerous blood cell. Support vector machine (SVM classifier) is used. The methodology is done by using Machine leraning with the aid of Matlab Software. Automatic detection of leukemia using microscopic human blood sample images and to classify the primary types of leukemia is the main goal of this method. The accuracy obtained is of 96.67%.