What are white blood cells
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Understanding White Blood Cells: Key Components of the Immune System
Introduction to White Blood Cells (WBCs)
White blood cells (WBCs), also known as leukocytes, are crucial components of the immune system. They play a vital role in defending the body against infections caused by viruses, bacteria, fungi, and other pathogens1 2 3. These cells are produced in the bone marrow and circulate through the blood and lymphatic systems3 7.
Types of White Blood Cells
WBCs are categorized into five main subtypes, each with specific functions and characteristics:
- Lymphocytes: These include T cells and B cells, which are essential for adaptive immunity, targeting specific pathogens and remembering them for faster response in future infections1 2 7.
- Monocytes: These cells differentiate into macrophages and dendritic cells, which are involved in phagocytosis and antigen presentation, respectively1 2 7.
- Neutrophils: The most abundant type of WBC, neutrophils are the first responders to microbial infection and are involved in phagocytosis1 2 7.
- Eosinophils: These cells combat multicellular parasites and are involved in allergic reactions1 2 7.
- Basophils: The least common type of WBC, basophils release histamine during allergic reactions and help defend against parasites1 2 7.
Importance of WBC Count
The number and types of WBCs in the blood provide critical information about an individual's health. Abnormal WBC counts can indicate various medical conditions, including infections, immune deficiencies, autoimmune diseases, and blood disorders such as leukemia1 2 3 5. For instance, a low WBC count, known as leukopenia, can reduce the body's ability to fight infections3.
Advances in WBC Classification and Detection
Deep Learning and Image Processing
Recent advancements in deep learning and image processing have significantly improved the accuracy and efficiency of WBC classification. Convolutional Neural Networks (CNNs) and other deep learning models have been employed to automatically identify and classify WBCs from blood images, achieving high accuracy rates1 2 3 4 7 8 9. For example, models like AlexNet, VGG16, ResNet50, and DenseNet have been used to extract features and classify WBCs with impressive success rates1 2 3 4 7 8 9.
Generative Adversarial Networks (GANs)
GANs have been utilized for data augmentation to address the challenge of limited training data, enhancing the generalization capabilities of WBC classifiers4. This approach allows for the creation of synthetic images that mimic the morphological variations of WBCs, improving the robustness of the classification models4.
Genetic and Genomic Studies
Genetic studies have identified multiple loci associated with WBC phenotypes, providing insights into the heritability and genetic factors influencing WBC counts and subtypes5. These findings help in understanding the genetic basis of immune responses and can aid in the development of personalized medical treatments.
Conclusion
White blood cells are indispensable to the immune system, protecting the body against a wide range of infections and diseases. Advances in deep learning and genetic research have enhanced our ability to classify and understand these cells, paving the way for improved diagnostic and therapeutic strategies. Accurate WBC classification and count are essential for diagnosing and managing various health conditions, highlighting the importance of continued research and technological development in this field.
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Most relevant research papers on this topic
White blood cell type identification using multi-layer convolutional features with an extreme-learning machine
The MLANet-FS-ELM model accurately identifies white blood cell types (Lymphocytes, Monocytes, Neutrophils, Eosinophils, and Basophils) with 99.99% training accuracy and 99.12% testing accuracy, outperforming alternative methods in the literature.
White blood cells detection and classification based on regional convolutional neural networks.
The study developed a computer-aided automated system that accurately detects and classifies white blood cell types in blood images, with ResNet50 showing the best performance with transfer learning.
Highly CitedClassification of white blood cells using deep features obtained from Convolutional Neural Network models based on the combination of feature selection methods
Using Convolutional Neural Network models with feature selection methods, and a combination of AlexNet, GoogLeNet, and ResNet-50, achieved a 97.95% success rate in white blood cell classification.
Highly CitedImproved Classification of White Blood Cells with the Generative Adversarial Network and Deep Convolutional Neural Network
The proposed method using generative adversarial networks and deep neural networks effectively classifies white blood cells into five types, with DenseNet-169 yielding a validation accuracy of 98.8%.
Multiple Loci Are Associated with White Blood Cell Phenotypes
Multiple genomic loci are associated with white blood cell count and subtypes, revealing functional relationships across cell types and diverse ancestral backgrounds.
Meta-AnalysisHighly CitedA Fully Unsupervised Instance Segmentation Technique for White Blood Cell Images
This paper proposes a novel instance segmentation method for identifying white blood cells in bone marrow images, revealing hidden infections and warning doctors about chronic medical conditions.
PreprintClassification of White Blood Cells: A Comprehensive Study Using Transfer Learning Based on Convolutional Neural Networks
DenseNet161 outperforms other deep learning models in accurately classifying white blood cells in blood film images, improving clinical laboratory procedures and monitoring human health.
Rigorous JournalAn Automated Multi-Level Convolutional Neural Network Approach for Classification of White Blood Cells
The proposed custom-built CNN framework accurately classifies white blood cell images with 98.70% accuracy, aiding medical professionals in diagnosing various abnormalities and disorders.
An Integrated Design based on Dual Thresholding and Features Optimization for White Blood Cells Detection
The proposed method accurately segments and classifies white blood cells at an early stage, achieving better outcomes compared to existing modern approaches.
White Blood Cell Membrane‐Coated Nanoparticles: Recent Development and Medical Applications
WBC membrane-coated nanoparticles show potential as versatile nanotherapeutics and tools for drug delivery, immune modulation, and tumor cell isolation in various medical fields.
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