Bone Marrow Cytomorphology Cell Detection using InceptionResNetV2

Raisa Fairooz Meem, Khandaker Tabin Hasan
5/9/2023
eess.IVcs.CV

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Abstract

Critical clinical decision points in haematology are influenced by the requirement of bone marrow cytology for a haematological diagnosis. Bone marrow cytology, however, is restricted to reference facilities with expertise, and linked to inter-observer variability which requires a long time to process that could result in a delayed or inaccurate diagnosis, leaving an unmet need for cutting-edge supporting technologies. This paper presents a novel transfer learning model for Bone Marrow Cell Detection to provide a solution to all the difficulties faced for the task along with considerable accuracy. The proposed model achieved 96.19\% accuracy which can be used in the future for analysis of other medical images in this domain.

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Cite this paper

@article{meem2023bone,
  title  = {Bone Marrow Cytomorphology Cell Detection using InceptionResNetV2},
  author = {Raisa Fairooz Meem and Khandaker Tabin Hasan},
  year   = {2023},
  eprint = {2305.05430},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2305.05430v1}
}

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