WBC image classification and generative models based on convolutional neural network.

Journal: BMC medical imaging
Published Date: May 20, 2022

Abstract

BACKGROUND: Computer-aided methods for analyzing white blood cells (WBC) are popular due to the complexity of the manual alternatives. Recent works have shown highly accurate segmentation and detection of white blood cells from microscopic blood images. However, the classification of the observed cells is still a challenge, in part due to the distribution of the five types that affect the condition of the immune system.

Authors

  • Changhun Jung
    Department of Cyber Security, Ewha Womans University, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul, 03760, Republic of Korea.
  • Mohammed Abuhamad
    Department of Computer Science, Loyola University Chicago, 1032 W Sheridan Rd, Chicago, 60660, USA.
  • David Mohaisen
    Department of Computer Science, University of Central Florida, 4000 Central Florida Blvd, Orlando, FL, 32816, USA.
  • Kyungja Han
    Department of Laboratory Medicine and College of Medicine, The Catholic University of Korea Seoul St. Mary's Hospital, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea.
  • DaeHun Nyang
    Department of Cyber Security, Ewha Womans University, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul, 03760, Republic of Korea. nyang@ewha.ac.kr.

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