A Study of the Classification Method of Bone Marrow Blood Cells Based on MobileVit


  • Manman Wang Tiangong University, School of Physical Science and Technology, TianJin,300387,CHN
  • Keke Shang Tiangong University, School of Physical Science and Technology, TianJin,300387,CHN
  • Haiming Zhang Tiangong University, School of Physical Science and Technology, TianJin,300387,CHN


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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How to Cite

Manman Wang, Keke Shang, & Haiming Zhang. (2022). A Study of the Classification Method of Bone Marrow Blood Cells Based on MobileVit. American Scientific Research Journal for Engineering, Technology, and Sciences, 88(1), 271–278. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/7705