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Yolov4 in White Blood Cell Classification

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Data Intelligence and Cognitive Informatics

Part of the book series: Algorithms for Intelligent Systems ((AIS))

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Abstract

White blood cell (WBC) counting is vital for the diagnostic of many diseases. However, the manual counting method operated in hospitals and centers is time-consuming and inefficient. Many automatic processes in classifying WBC types were proposed using deep learning (DL) models. YOLOv4 is an emerging model for detecting objects with promising results in many applications including the medical field. In this paper, YOLOv4’s performance would be tested on classifying four types of WBC: monocyte, lymphocyte, neutrophil, and eosinophil. A mixed database of WBC microscopic images from an online dataset BCCD and a hospital dataset collected from the Vietnamese National Institute of Hematology and Blood Transfusion, comprising of 10,275 images in total after the augmentation, was used for training and testing the model. The results showed that the trained YOLOv4 was able to classify equivalently well all 4 WBC types with the average accuracy of 97.8%, ranking the second-best option when compared to other contemporary studies.

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Author information

Authors and Affiliations

  1. Hanoi University of Science and Technology, Hanoi, Vietnam

    Luong Duong Trong, Hung Pham Manh & Duc Nguyen Minh

  2. Equipment Institute and Public Heath, Hanoi, Vietnam

    Tung Pham Thanh

Authors
  1. Luong Duong Trong
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  2. Tung Pham Thanh
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  3. Hung Pham Manh
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  4. Duc Nguyen Minh
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Corresponding author

Correspondence to Luong Duong Trong .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, GITAM University, Bangalore, Karnataka, India

    I. Jeena Jacob

  2. Department of Mathematics and Computer Science, Ashland University, River Forest, IL, USA

    Selvanayaki Kolandapalayam Shanmugam

  3. Department of Artificial Intelligence, Lviv Polytechnic National University, Lviv, Ukraine

    Ivan Izonin

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Trong, L.D., Thanh, T.P., Manh, H.P., Minh, D.N. (2023). Yolov4 in White Blood Cell Classification. In: Jacob, I.J., Kolandapalayam Shanmugam, S., Izonin, I. (eds) Data Intelligence and Cognitive Informatics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-6004-8_31

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