Deep Learning Approaches for Enhanced White Blood Cell Subtype Classification
DOI:
https://doi.org/10.48047/Keywords:
WBC classification, Historical images, CNN.Abstract
White blood cells (WBCs), or leukocytes, are a crucial component of the immune system, characterized by their nuclei and absence of hemoglobin. They play a vital role in defending the body against foreign microorganisms, such as bacteria and viruses, through processes like phagocytosis and antibody production. Leukocytes are categorized into five main types: neutrophils, eosinophils, lymphocytes, monocytes, and basophils. Neutrophils, the most abundant type, are primarily responsible for combating bacterial and fungal infections. Eosinophils (2–4% of WBCs) respond to allergies and parasitic infections, while lymphocytes are essential for the specific recognition and elimination of foreign agents. Monocytes facilitate the direct destruction of pathogens and assist in debris cleanup at infection sites.
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References
C. Shorten and T. Khoshgoftaar, "A survey on Image Data Augmentation for Deep Learning", Journal of Big Data, vol. 6, no. 1, 2019. Available: 10.1186/s40537-019-0197-0.
"The American Society of Hematology", Hematology.org, 2020. [Online]. Available: https://www.hematology.org. [Accessed: 28- Nov- 2019].
AL-Dulaimi, Khamael, et al. "Classification of white blood cell types from microscope images: Techniques and challenges." Microscopy Science: Last Approaches on Educational Programs and Applied Research. Vol. 8. Formatex Research Center, 2018.
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