Classification of Leucocytes Using Deep Learning

Suganthi, N.

doi:10.21786/bbrc/13.11/25

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2023

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“…We anticipate that CNN will merge. The purpose of this work is to develop a computerized [17] WBC categorization system based on deep learning. By optimizing ResNet, Inception, and VGG Net, transfer learning has been incorporated into many of the models that have been proposed so far for this application.…”

Section: Literature Surveymentioning

confidence: 99%

Leukocytes Classification Using Convolutional Neural Network

Bushra¹,

Sheeba²,

Subasini³

et al. 2023

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Maintaining a healthy life is very important in today’s world. Our body has ability to fight against contagious diseases with the aid of white blood corpuscles (WBC) which generates natural immune system. Preserving a good WBC count is crucial as it leads to various hematological problems, one among them is Leukemia, a condition which results in blood cancer, huge accumulation of WBC cells in bone marrow, an abnormal growth of WBC cells, hinders natural immune system fighting against infectious diseases. White blood cells can be categorised into Eosinophils, Lymphocytes, Monocytes, Neutrophils and Basophils. In this study, a pre-trained Convolutional neural network architecture called Le Net is used to automatically classify WBC cells. It efficiently classifies WBC cells from the given input sample blood cell images compared to other pre trained models such as Alex-Net and custom-built CNN called white capsule net. The hyper parameters Le Net are fine tuned to yield higher accuracy of 96%.

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Section: Literature Surveymentioning

confidence: 99%