Classification of chronic myeloid leukemia cell subtypes based on microscopic image analysis

Authors

  • Narjes Ghane Department of Bioelectrics and Biomedical Engineering, School of Advanced Technologies in Medicine and Student Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
  • Alireza Vard Department of Bioelectrics and Biomedical Engineering, School of Advanced Technologies in Medicine and Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran. Post Code: 81746-73461. Tel: +98 31 37923859; Fax: +98 31 37923851; E-mail: vard@amt.mui.ac.ir, alivard@gmail.com
  • Ardeshir Talebi Department of Pathology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
  • Pardis Nematollahy Department of Pathology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

DOI:

https://doi.org/10.17179/excli2019-1292

Keywords:

Chronic Myeloid Leukemia (CML), blood cancer, microscopic image processing, classification, decision tree classifier

Abstract

This paper presents a simple and efficient computer-aided diagnosis method to classify Chronic Myeloid Leukemia (CML) cells based on microscopic image processing. In the proposed method, a novel combination of both typical and new features is introduced for classification of CML cells. Next, an effective decision tree classifier is proposed to classify CML cells into eight groups. The proposed method was evaluated on 1730 CML cell images containing 714 cells of non-cancerous bone marrow aspiration and 1016 cells of cancerous peripheral blood smears. The performance of the proposed classification method was compared to manual labels made by two experts. The average values of accuracy, specificity and sensitivity were 99.0 %, 99.4 % and 98.3 %, respectively for all groups of CML. In addition, Cohen's kappa coefficient demonstrated high conformity, 0.99, between joint diagnostic results of two experts and the obtained results of the proposed approach. According to the obtained results, the suggested method has a high capability to classify effective cells of CML and can be applied as a simple, affordable and reliable computer-aided diagnosis tool to help pathologists to diagnose CML.

Published

2019-06-14

How to Cite

Ghane, N., Vard, A., Talebi, A., & Nematollahy, P. (2019). Classification of chronic myeloid leukemia cell subtypes based on microscopic image analysis. EXCLI Journal, 18, 382–404. https://doi.org/10.17179/excli2019-1292

Issue

Section

Original articles

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