RT Journal Article
T1 Digital Microscopy Augmented by Artificial Intelligence toInterpret Bone Marrow Samples for Hematological Diseases 
A1 Bermejo Peláez, David
A1 Rueda Charro, Sandra
A1 García Roa, María
A1 Trelles Martínez, Roberto
A1 Bobes-Fernández, Alejandro
A1 Hidalgo Soto, Marta
A1 García-Vicente, Roberto
A1 Morales Fernández, María Luz
A1 Rodríguez García, Alba
A1 Ortiz Ruiz, Alejandra
A1 Blanco Sánchez, Alberto
A1 Mousa Urbina, Adriana
A1 Álamo García-Donas, Elisa
A1 Lin, Lin
A1 Dacal Picazo, Elena
A1 Cuadrado Sánchez, Daniel
A1 Postigo Camps, María
A1 Vladimirov, Alexander
A1 García-Villena, Jaime
A1 Santos Torres, Andrés
A1 Ledesma-Carbayo, Maria Jesús
A1 Ayala Díaz, Rosa María
A1 Martínez López, Joaquín
A1 Linares Gómez, María
A1 Luengo Oroz, Miguel
AB Analysis of bone marrow aspirates (BMA) is an essential step in the diagnosis of hematological disorders. This analysis is usually performed based on visual examination of the 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 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 (DCC) process and reduces inter-observer variability. It has been designed to integrate AI algorithms with the daily clinical routine and can be used in any regular hospital workflow.
SN 1431-9276
YR 2022
FD 2022-08-30
LK https://hdl.handle.net/20.500.14352/101540
UL https://hdl.handle.net/20.500.14352/101540
LA eng
NO Bermejo-Peláez D, Charro SR, Roa MG, Trelles-Martínez R, Bobes-Fernández A, Soto MH, García-Vicente R, Morales ML, Rodríguez-García A, Ortiz-Ruiz A, Sánchez AB, Urbina AM, Álamo E, Lin L, Dacal E, Cuadrado D, Postigo M, Vladimirov A, Garcia-Villena J, Santos A, Ledesma-Carbayo MJ, Díaz RA, Martínez-López J, Linares M, Luengo-Oroz M. Digital system augmented by artificial intelligence to interpret bone marrow samples for hematological disease diagnosis 2022. https://doi.org/10.1101/2022.08.30.22279373.
NO Horizon 2020
NO Agencia Estatal de Investigación (España)
NO Ministerio de Ciencia, Innovación y Universidades (España)
NO Sociedad Española de Hematología y Hemoterapia
NO Comunidad de Madrid
DS Docta Complutense
RD 4 abr 2025