Data for assessing red blood cell deformability from microscopy images using deep learning

Erik S. Lamoureux; Emel Islamzada; Matthew V.J. Wiens; Kerryn Matthews; Simon P. Duffy; Hongshen Ma

Data in Brief (Apr 2023)

Data for assessing red blood cell deformability from microscopy images using deep learning

Erik S. Lamoureux,
Emel Islamzada,
Matthew V.J. Wiens,
Kerryn Matthews,
Simon P. Duffy,
Hongshen Ma

Affiliations

Erik S. Lamoureux: Department of Mechanical Engineering, University of British Columbia, 2054-6250 Applied Science Lane, Vancouver, BC V6T 1Z4, Canada; Centre for Blood Research, University of British Columbia, 4th Floor, 2350 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada
Emel Islamzada: Centre for Blood Research, University of British Columbia, 4th Floor, 2350 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, 105-2211 Wesbrook Mall, Vancouver, BC V6T 2B5, Canada
Matthew V.J. Wiens: School of Biomedical Engineering, University of British Columbia, 2222 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada
Kerryn Matthews: Department of Mechanical Engineering, University of British Columbia, 2054-6250 Applied Science Lane, Vancouver, BC V6T 1Z4, Canada; Centre for Blood Research, University of British Columbia, 4th Floor, 2350 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada
Simon P. Duffy: Department of Mechanical Engineering, University of British Columbia, 2054-6250 Applied Science Lane, Vancouver, BC V6T 1Z4, Canada; Centre for Blood Research, University of British Columbia, 4th Floor, 2350 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada; British Columbia Institute of Technology, 3700 Willingdon Ave, Burnaby, BC V5G 3H2, Canada
Hongshen Ma: Department of Mechanical Engineering, University of British Columbia, 2054-6250 Applied Science Lane, Vancouver, BC V6T 1Z4, Canada; Centre for Blood Research, University of British Columbia, 4th Floor, 2350 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada; School of Biomedical Engineering, University of British Columbia, 2222 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada; Vancouver Prostate Centre, Vancouver General Hospital, 2660 Oak Street, Vancouver, BC V6H 3Z6, Canada; Corresponding author.

Journal volume & issue: Vol. 47
p. 108928

Abstract

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Red blood cell (RBC) deformability is a vital biophysical property that dictates the ability of these cells to repeatedly squeeze through small capillaries in the microvasculature. This capability is known to differ between individuals and degrades due to natural aging, pathology, and cold storage. There is great interest in measuring RBC deformability because this parameter is a potential biomarker of RBC quality for use in blood transfusions. Measuring this property from microscopy images would greatly reduce the effort required to acquire this information, as well as improve standardization across different centers. This dataset consists of live cell microscopy images of RBC samples from 10 healthy donors. Each RBC sample is sorted into fractions based on deformability using the microfluidic ratchet device. Each deformability fraction is imaged in microwell plates using a Nikon CFI S Plan Fluor ELWD 40 × objective and a Nikon DS-Qi2 CMOS camera on a Nikon Ti-2E inverted microscope. This data could be reused to develop deep learning algorithms to associate live cell images with cell deformability.

Published in Data in Brief

ISSN: 2352-3409 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Medicine: Medicine (General): Computer applications to medicine. Medical informatics; Science: Science (General)
Website: http://www.journals.elsevier.com/data-in-brief/

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