This paper is published in Volume-3, Issue-6, 2017
Area
Blood Cancer
Author
Sachin Paswan, Yogesh Kumar Rathore
Org/Univ
Raipur Institute of Technology, Raipur, Chhattisgarh, India
Pub. Date
15 November, 2017
Paper ID
V3I6-1237
Publisher
Keywords
Automated Leukemia Detection, Acute Lymphoblastic Leukemia, Lymphocyte Image Segmentation, Machine Learning

Citationsacebook

IEEE
Sachin Paswan, Yogesh Kumar Rathore. Detection and Classification of Blood Cancer from Microscopic Cell Images Using SVM KNN and NN Classifier, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Sachin Paswan, Yogesh Kumar Rathore (2017). Detection and Classification of Blood Cancer from Microscopic Cell Images Using SVM KNN and NN Classifier. International Journal of Advance Research, Ideas and Innovations in Technology, 3(6) www.IJARIIT.com.

MLA
Sachin Paswan, Yogesh Kumar Rathore. "Detection and Classification of Blood Cancer from Microscopic Cell Images Using SVM KNN and NN Classifier." International Journal of Advance Research, Ideas and Innovations in Technology 3.6 (2017). www.IJARIIT.com.

Abstract

Leukemia is a cancer of the blood and bone marrow, the spongy tissue confidential the bones where blood cells are made. Acute myeloid leukemia (AML) is one of the most common types of leukemia among adults. The signs and symptoms of leukemia are non-specific in nature and also they are comparable to the symptoms of other mutual disorders. Manual microscopic inspection of stained blood smear or bone marrow aspirate is the only way to an effective diagnosis of leukemia. But this method is time-consuming and less accurate. In this paper, a technique for automatic detection and classification of AML in blood smear is presented. K-means algorithm is used for segmentation. KNN, NN and SVM are used for classification. GLCM is used for optimising the spectral features. The local binary pattern is used for texture description. Blood microscope images were tested and the performance of the classifier was analyzed.