Classification of White Blood Cell Images Using Probabilistic Neural Networks

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@article{1702204,
      author = {Gummadidala Asha, Adapa Deepthi, Bandaru Sowmya, Ajimeera Kaveri Bai, Dr. Pulagam Ammi Reddy},
      title = {Classification of White Blood Cell Images Using Probabilistic Neural Networks},
      journal = {Iconic Research And Engineering Journals},
      year = {2020},
      volume = {3},
      number = {10},
      pages = {167-172},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1702204.pdf},
      abstract = {Numerous diseases can be diagnosed based on the number of cells for each class of white blood cells in the blood. Therefore, extracting information about that is considered very important for haematologists . The density of WBC?s in our blood stream provides a glimpse into state of our immune system. There are five types of WBC?s. They are Neutrophil, Eosinophil, Basophil, Monocyte and Lymphocyte. This project presents a better way to classify the White Blood Cells. The proposed method is implemented with the help of K Means clustering with Probabilistic Neural Networks (PNN) classifier .The proposed K Means clustering with PNN classifier gives better results.},
      keywords = {White Blood Cells(WBCs), Neutrophil, Eosinophil, Basophil, Monocyte, Lymphocyte, K Means clustering, Probabilistic Neural Networks (PNN)},
      month = {April},
  }