Automatic Detection of Acute Myeloid Leukemia from Microscopic Blood Smear Image

Kumar, Preetham and Udwadia, Marzban H (2017) Automatic Detection of Acute Myeloid Leukemia from Microscopic Blood Smear Image. In: International Conference on Advances in Computing, Communications and Informatics, 13/09/2017, MIT, Manipal.

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Cancer of blood-forming tissues is called Leukemia. This disease hinders the body’s ability to fight infection. Leukemia can be categorized into many types. Acute Lymphoblastic Leukemia (ALL) and Acute Myeloid Leukemia (AML) are the two main types. The blood cells’ growth and bone marrow are affected by AML. Collection of myeloid blasts in the bone marrow is one of the main characteristics of AML. In this research, a novel method is analyzed to detect the presence of AML. The paper proposes a technique that automatically detects and segments the nucleus from white blood cells (WBCs) in the microscopic blood smear images. Segmentation and clustering is done using a K-Means algorithm, while classification is done using Support Vector Machine (SVM) with feature reduction.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Acute Myeloid Leukemia, Classification,Feature Extraction, K-Means Clustering, Support Vector Machine.
Subjects: Engineering > MIT Manipal > Information and Communication Technology
Depositing User: MIT Library
Date Deposited: 14 Jul 2018 09:12
Last Modified: 14 Jul 2018 09:12

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