Bone Marrow Cytomorphology Cell Detection using InceptionResNetV2

• URL: http://arxiv.org/abs/2305.05430v1
• Date: Tue, 9 May 2023 13:18:35 GMT
• Title: Bone Marrow Cytomorphology Cell Detection using InceptionResNetV2
• Authors: Raisa Fairooz Meem, Khandaker Tabin Hasan
• Abstract summary: This paper presents a novel transfer learning model for Bone Marrow Cell Detection. The proposed model achieved 96.19% accuracy which can be used in the future for analysis of other medical images in this domain.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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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