Journal of Carcinogenesis & Mutagenesis

Abstract

Bone Marrow Cytomorphology Cell Detection using InceptionResNetV2

Raisa Fairooz Meem* and Khandaker Tabin Hasan

Purpose: Critical decision points in the field of hematology heavily rely on the inclusion of bone marrow cytology for diagnosing haematological conditions. However, the utilization of bone marrow cytology is limited to specialized reference facilities with expert knowledge, resulting in significant inter-observer variability and time-consuming processing. These limitations can potentially lead to delayed or inaccurate diagnoses, highlighting the urgent need for state-of-the-art supporting technologies.

Methods: This research paper introduces a transfer learning model using InceptionResNetV2 specifically developed for the detection of bone marrow cells, offering a comprehensive solution to address the existing challenges in this area.

Results: The proposed model demonstrates an impressive accuracy rate of 96.19%, making it a valuable tool for analyzing medical images in this domain.

Conclusion: The success of this experiment plays an important role in future applications and advancements in the field of haematology research.

Published Date: 2023-11-13; Received Date: 2023-10-11