Identification of Leukemia Subtypes from Microscopic Images Using Convolutional Neural Network
Department of Computer Engineering, Dokuz Eylul University, 35160 Izmir, Turkey
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Diagnostics 2019, 9(3), 104; https://doi.org/10.3390/diagnostics9030104
Received: 2 June 2019
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Revised: 22 August 2019
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Accepted: 23 August 2019
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Published: 25 August 2019
(This article belongs to the Section Medical Imaging and Theranostics)
Leukemia is a fatal cancer and has two main types: Acute and chronic. Each type has two more subtypes: Lymphoid and myeloid. Hence, in total, there are four subtypes of leukemia. This study proposes a new approach for diagnosis of all subtypes of leukemia from microscopic blood cell images using convolutional neural networks (CNN), which requires a large training data set. Therefore, we also investigated the effects of data augmentation for an increasing number of training samples synthetically. We used two publicly available leukemia data sources: ALL-IDB and ASH Image Bank. Next, we applied seven different image transformation techniques as data augmentation. We designed a CNN architecture capable of recognizing all subtypes of leukemia. Besides, we also explored other well-known machine learning algorithms such as naive Bayes, support vector machine, k-nearest neighbor, and decision tree. To evaluate our approach, we set up a set of experiments and used 5-fold cross-validation. The results we obtained from experiments showed that our CNN model performance has 88.25% and 81.74% accuracy, in leukemia versus healthy and multi-class classification of all subtypes, respectively. Finally, we also showed that the CNN model has a better performance than other well-known machine learning algorithms.
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Keywords:
leukemia diagnosis; recognizing leukemia subtypes; multi-class classification; microscopic blood cells images; data augmentation; deep learning; convolutional neural network
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MDPI and ACS Style
Ahmed, N.; Yigit, A.; Isik, Z.; Alpkocak, A. Identification of Leukemia Subtypes from Microscopic Images Using Convolutional Neural Network. Diagnostics 2019, 9, 104. https://doi.org/10.3390/diagnostics9030104
AMA Style
Ahmed N, Yigit A, Isik Z, Alpkocak A. Identification of Leukemia Subtypes from Microscopic Images Using Convolutional Neural Network. Diagnostics. 2019; 9(3):104. https://doi.org/10.3390/diagnostics9030104
Chicago/Turabian StyleAhmed, Nizar, Altug Yigit, Zerrin Isik, and Adil Alpkocak. 2019. "Identification of Leukemia Subtypes from Microscopic Images Using Convolutional Neural Network" Diagnostics 9, no. 3: 104. https://doi.org/10.3390/diagnostics9030104
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