Automatic detection of Acute Myeloid Leukemia from microscopic blood smear image

Preetham Kumar, Shazad Maneck Udwadia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publication2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1803-1808
Number of pages6
Volume2017-January
ISBN (Electronic)9781509063673
DOIs
Publication statusPublished - 30-11-2017
Event2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017 - Manipal, Mangalore, India
Duration: 13-09-201716-09-2017

Conference

Conference2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017
CountryIndia
CityManipal, Mangalore
Period13-09-1716-09-17

Fingerprint

Blood
Bone
Cell growth
Support vector machines
Cells
Tissue

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

Cite this

Kumar, P., & Udwadia, S. M. (2017). Automatic detection of Acute Myeloid Leukemia from microscopic blood smear image. In 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017 (Vol. 2017-January, pp. 1803-1808). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACCI.2017.8126106
Kumar, Preetham ; Udwadia, Shazad Maneck. / Automatic detection of Acute Myeloid Leukemia from microscopic blood smear image. 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1803-1808
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Kumar, P & Udwadia, SM 2017, Automatic detection of Acute Myeloid Leukemia from microscopic blood smear image. in 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 1803-1808, 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017, Manipal, Mangalore, India, 13-09-17. https://doi.org/10.1109/ICACCI.2017.8126106

Automatic detection of Acute Myeloid Leukemia from microscopic blood smear image. / Kumar, Preetham; Udwadia, Shazad Maneck.

2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 1803-1808.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - 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.

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Kumar P, Udwadia SM. Automatic detection of Acute Myeloid Leukemia from microscopic blood smear image. In 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. Vol. 2017-January. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1803-1808 https://doi.org/10.1109/ICACCI.2017.8126106