Do white blood cells have a nucleus
Pro Research Analysisby 
Searched over 200M research papers
Do White Blood Cells Have a Nucleus?
Presence of Nucleus in White Blood Cells
White blood cells (WBCs), also known as leukocytes, are a crucial component of the human immune system. Unlike red blood cells, which lack a nucleus, white blood cells do indeed have a nucleus. The nucleus of a white blood cell can vary in shape, ranging from round to kidney-shaped, and can even have multiple lobes as the cell matures1.
Importance of the Nucleus in White Blood Cells
The nucleus of white blood cells plays a significant role in their detection and classification. Accurate segmentation and analysis of the nucleus are essential for diagnosing various blood-related diseases. For instance, the morphological properties of the WBC nucleus are critical for classifying different types of WBCs and identifying abnormalities2 3.
Methods for Nucleus Segmentation
Several advanced methods have been developed to segment and analyze the nucleus of white blood cells. One such method involves using Otsu’s thresholding-based technique, which has shown high accuracy in detecting the nucleus2. Another approach employs color space conversion and k-means algorithm to localize and segment the nucleus, achieving high accuracy in classification tasks3.
Nucleus and Disease Diagnosis
The nucleus of white blood cells contains chromosomes and other structures like chromatin and nucleolus, which are essential for diagnosing diseases such as leukemia. The presence of giant nuclei and nucleoli in WBCs can be indicative of leukemia, although additional symptoms must also be considered4. Advanced image processing techniques, such as curvelet transform, are used to detect these features and aid in the diagnosis4.
Conclusion
In summary, white blood cells do have a nucleus, which is vital for their function and classification. The nucleus's shape and structure are key indicators in diagnosing various blood-related diseases. Advanced segmentation and analysis techniques are crucial for accurately identifying and classifying white blood cells based on their nuclear properties.
Sources and full results
Most relevant research papers on this topic
Automatic Recognition of White Blood Cells
Differentiating white blood cells is crucial in medicine, as they play a crucial role in detecting infections and preventing diseases.
Easy-GT: Open-Source Software to Facilitate Making the Ground Truth for White Blood Cells Nucleus
Easy-GT is an intelligent open-source software that speeds up creating ground truth for white blood cells' nucleus faster and easier, using Otsu's thresholding-based method and a dice similarity coefficient of 95.42 %.
PreprintAn Automatic Nucleus Segmentation and CNN Model based Classification Method of White Blood Cell
Our new nucleus segmentation method and CNN model effectively classify white blood cells, achieving 96% overall accuracy on the BCCD test database.
Highly CitedExtraction of Nucleolus Candidate Zone in White Blood Cells of Peripheral Blood Smear Images Using Curvelet Transform
Curvelet transform effectively detects nucleolus candidate zones in white blood cells, aiding in diagnosis of leukemia and atypical cells.
Semiautomatic White Blood Cell Segmentation Based on Multiscale Analysis
This paper presents novel methods for semiautomatic white blood cell segmentation, enhancing accuracy in automatic differential counting and disease diagnosis.
Highly CitedDeep Features Aggregation-Based Joint Segmentation of Cytoplasm and Nuclei in White Blood Cells
The LDS-Net and LDAS-Net shallow networks effectively segment cytoplasm and nuclei in white blood cells, outperforming state-of-the-art methods with superior computational efficiency and requiring only 6.5 million trainable parameters.
New segmentation and feature extraction algorithm for classification of white blood cells in peripheral smear images
The proposed method accurately classifies white blood cells in peripheral smear images with a 94.65 % accuracies in Raabin-WBC, LISC, and BCCD datasets.
Rigorous JournalA Framework for White Blood Cell Segmentation in Microscopic Blood Images Using Digital Image Processing
The proposed framework effectively segments white blood cells into nucleus and cytoplasm regions, improving hematologists' analysis and diagnosis of diseases like acute leukemia.
Highly CitedMorphological Granulometric Features of Nucleus in Automatic Bone Marrow White Blood Cell Classification
Nucleus-based features alone can achieve a 77% classification rate in automatic bone marrow white blood cell classification, making it easier to segment white blood cells in high density areas.
Highly Cited