Publication date
1 Feb 2024
Published in
Microscopy and Microanalysis
Keywords
hematology,
Citation
David Bermejo-Peláez, Sandra Rueda Charro, María García Roa, Roberto Trelles-Martínez, Alejandro Bobes-Fernández, Marta Hidalgo Soto, Roberto García-Vicente, María Luz Morales, Alba Rodríguez-García, Alejandra Ortiz-Ruiz, Alberto Blanco Sánchez, Adriana Mousa Urbina, Elisa Álamo, Lin Lin, Elena Dacal, Daniel Cuadrado, María Postigo, Alexander Vladimirov, Jaime Garcia-Villena, Andrés Santos, María Jesús Ledesma-Carbayo, Rosa Ayala, Joaquín Martínez-López, María Linares, Miguel Luengo-Oroz, Digital Microscopy Augmented by Artificial Intelligence to Interpret Bone Marrow Samples for Hematological Diseases, Microscopy and Microanalysis, Volume 30, Issue 1, February 2024, Pages 151–159
ABSTRACT
Analysis of bone marrow aspirates (BMAs) is an essential step in the diagnosis of hematological disorders. This analysis is usually performed based on a visual examination of samples under a conventional optical microscope, which involves a labor-intensive process, limited by clinical experience and subject to high observer variability. In this work, we present a comprehensive digital microscopy system that enables BMA analysis for cell type counting and differentiation in an efficient and objective manner. This system not only provides an accessible and simple method to digitize, store, and analyze BMA samples remotely but is also supported by an Artificial Intelligence (AI) pipeline that accelerates the differential cell counting process and reduces interobserver variability. It has been designed to integrate AI algorithms with the daily clinical routine and can be used in any regular hospital workflow.