Segmentation and Classification Techniques of Acute Myeloid Leukemia using Image Processing: A Survey

Authors

  • Kishan Patel  Department of Computer Engineering, S.V.I.T. Vasad, Gujarat, India
  • Rashmin B. Prajapati  Department of Computer Engineering, S.V.I.T. Vasad, Gujarat, India

Keywords:

Acute Myeloid Leukemia (AML), Segmentation, Feature Extraction, Classification

Abstract

The White blood cells or Leukocytes plays a major role in the diagnosis of different diseases (including leukemia). Leukemia is a type of blood disease or so-called cancer of the blood that begins in the bone marrow and usually caused by an excessive alterations in the production of malignant and immature white blood cells. Acute Myeloid leukemia (AML) is a subtype of acute leukemia, which is characterized by the accumulation of myeloid blasts in the bone marrow. Subtypes of AML i.e., M0–M7. AML is also called as Acute Myelogenous Leukemia, Acute Meroblastic Leukemia, Acute Granulocytic Leukemia and Acute No lymphocytic Leukemia. This paper provides a survey of several segmentation and classification techniques for detection of acute myeloid leukemia using image processing.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-02-28

Issue

Volume 3, Issue 1, January-February-2018

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Kishan Patel, Rashmin B. Prajapati, " Segmentation and Classification Techniques of Acute Myeloid Leukemia using Image Processing: A Survey, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.623-628, January-February-2018.