A Study of the Classification Method of Bone Marrow Blood Cells Based on MobileVit
Keywords:classification of bone marrow blood cells, morphological diagnosis, Deep learning，MobileVit, classification accuracy
The automatic classification of bone marrow blood cells is of great significance to diagnosis of acute leukemia. We applied the MobileVit network model to morphological classification of bone marrow cells by using transformer based on self-attention mechanism as convolution for global representation and achieve a global representation with reduced calculation parameters. We found that in the bone marrow blood cell classification task, without the use of transfer learning, MobileVit classification achieved 97% accuracy, exceeding the classification accuracy of Resnet and Densenet networks, and reducing FLOPS and params significantly. Compared to other lightweight networks, the MobileVit model demonstrates improved accuracy and comparable FLOPS and params.
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