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Computer-Aided Acute Lymphoblastic Leukemia Diagnosis System Based on Image Analysis

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Advances in Soft Computing and Machine Learning in Image Processing

Part of the book series: Studies in Computational Intelligence ((SCI,volume 730))

Abstract

Leukemia is a kind of cancer that basically begins in the bone marrow. It is caused by excessive production of leukocytes that replace normal blood cells. This chapter presents Computer-Aided Acute Lymphoblastic Leukemia (ALL) diagnosis system based on image analysis. It presented to identify the cells ALL by segmenting each cell in the microscopic images, and then classify each segmented cell to be normal or affected. A well-known dataset was used in this chapter (ALL-IDB2). The dataset contains 260 cell images: 130 normal and 130 affected by ALL. The proposed system starts by segmenting the white blood cells. This process includes sub-processes such as conversion from RGB to CMYK color model, histogram equalization, thresholding by Zack technique, and background removal operation. Then some features were extracted from each cell, each of them represents aspects of a cell. The extracted features include color, texture, and shape features. Then each feature set was exposed to three data normalization techniques z-score, min-max, and grey-scaling to narrow down the gap between the features values. Finally, different classifiers were used to validate the proposed system. The proposed diagnosing system achieved acceptable accuracies when tested by well-known classifiers; however, K-NN achieved the best classification accuracy.

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Author information

Authors and Affiliations

  1. Culture & Science City, 6th of October, 15525, Egypt

    Ahmed M. Abdeldaim

  2. Damietta University, Damietta, 34517, Egypt

    Ahmed T. Sahlol

  3. Mansoura University, Mansoura, Egypt

    Mohamed Elhoseny

  4. Faculty of Computers and Information, Information Technology Department, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  5. Scientific Research Group in Egypt (SRGE), Cairo, Egypt

    Ahmed M. Abdeldaim, Ahmed T. Sahlol, Mohamed Elhoseny & Aboul Ella Hassanien

Authors
  1. Ahmed M. Abdeldaim
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  2. Ahmed T. Sahlol
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  3. Mohamed Elhoseny
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  4. Aboul Ella Hassanien
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Corresponding author

Correspondence to Ahmed T. Sahlol .

Editor information

Editors and Affiliations

  1. Faculty of Computers and Information, Information Technology Department, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. CUCEI, Departamento de Ciencias Computacionales, Universidad de Guadalajara, Guadalajara, Mexico

    Diego Alberto Oliva

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Abdeldaim, A.M., Sahlol, A.T., Elhoseny, M., Hassanien, A.E. (2018). Computer-Aided Acute Lymphoblastic Leukemia Diagnosis System Based on Image Analysis. In: Hassanien, A., Oliva, D. (eds) Advances in Soft Computing and Machine Learning in Image Processing. Studies in Computational Intelligence, vol 730. Springer, Cham. https://doi.org/10.1007/978-3-319-63754-9_7

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  • DOI: https://doi.org/10.1007/978-3-319-63754-9_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63753-2

  • Online ISBN: 978-3-319-63754-9

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