Research Article
White Blood Cells Classification using CNN
@ARTICLE{10.4108/eetpht.9.4852, author={Jinka Chandra Kiran and Beebi Naseeba and Abbaraju Sai Sathwik and Thadikala Prakash Badrinath Reddy and Kokkula Lokesh and Tatigunta Bhavi Teja Reddy and Nagendra Panini Challa}, title={White Blood Cells Classification using CNN}, journal={EAI Endorsed Transactions on Pervasive Health and Technology}, volume={9}, number={1}, publisher={EAI}, journal_a={PHAT}, year={2024}, month={1}, keywords={Classification, Machine Learning, SVM, CNN, ANN, KNN}, doi={10.4108/eetpht.9.4852} }- Jinka Chandra Kiran
Beebi Naseeba
Abbaraju Sai Sathwik
Thadikala Prakash Badrinath Reddy
Kokkula Lokesh
Tatigunta Bhavi Teja Reddy
Nagendra Panini Challa
Year: 2024
White Blood Cells Classification using CNN
PHAT
EAI
DOI: 10.4108/eetpht.9.4852
Abstract
One kind of cancer that arises from an overabundance of white blood cells produced by the patient's bone marrow and lymph nodes is leukaemia. Since white blood cells are the primary source of immunity, or the body's defence, it is imperative to determine the type of leukocyte cell the patient has leukaemia from as soon as possible. Failure to do so could result in a more serious condition. Haematologists typically use a light microscope to examine the necessary cell traces in order to classify and identify the features of the cell cytoplasm or nucleus in order to diagnose leukaemia in a patient. One form of cancer is leukaemia, which develops when a patient's bone marrow and lymph nodes produce an excessive amount of white blood cells. It is vital to determine the type of leukocyte cell the patient has leukaemia from as soon as possible because postponing diagnosis can worsen the situation. Our white corpuscles are the primary source of immunity, which is the body's defence. In order to define and identify the features found in the cell cytoplasm or nucleus, hematopathologists typically use a light microscope to examine the necessary cell traces in order to diagnose leukaemia in patients.
Copyright © 2024 J. C. Kiran et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
