Automated Decision Support System for Detection of Leukemia from Peripheral Blood Smear Images

Hegde, Roopa B and Prasad, Keerthana and Hebbar, Harishchandra N and Singh, Brij Mohan Kumar (2020) Automated Decision Support System for Detection of Leukemia from Peripheral Blood Smear Images. Journal of Digital Imaging, 33. pp. 361-374. ISSN 0897-1889

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Abstract

Peripheral blood smear analysis plays a vital role in diagnosing many diseases including cancer. Leukemia is a type of cancer which begins in bone marrow and results in increased number of white blood cells in peripheral blood. Unusual variations in appearance of white blood cells indicate leukemia. In this paper, an automated method for detection of leukemia using image processing approach is proposed. In the present study, 1159 images of different brightness levels and color shades were acquired from Leishman stained peripheral blood smears. SVM classifier was used for classification of white blood cells into normal and abnormal, and also for detection of leukemic WBCs from the abnormal class. Classification of the normal white blood cells into five sub-types was performed using NN classifier. Overall classification accuracy of 98.8% was obtained using the combination of NN and SVM.

Item Type: Article
Uncontrolled Keywords: Peripheral blood smear analysis · Leukemia · Computer aided detection · Classification
Subjects: Information Sciences > MCIS Manipal
Medicine > KMC Manipal > Pathology
Depositing User: MIT Library
Date Deposited: 27 Jun 2020 10:34
Last Modified: 27 Jun 2020 10:34
URI: http://eprints.manipal.edu/id/eprint/155366

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