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Image processing and machine learning in the morphological analysis of blood cells

Author
Rodellar, J.; Alferez, E.; Acevedo, A.; Molina, Á.; Merino, A.
Type of activity
Journal article
Journal
International journal of laboratory hematology
Date of publication
2018-05-01
Volume
40
Number
S1
First page
46
Last page
53
DOI
https://doi.org/10.1111/ijlh.12818 Open in new window
Repository
http://hdl.handle.net/2117/117690 Open in new window
URL
https://onlinelibrary.wiley.com/doi/abs/10.1111/ijlh.12818 Open in new window
Abstract
Introduction This review focuses on how image processing and machine learning can be useful for the morphological characterization and automatic recognition of cell images captured from peripheral blood smears. Methods The basics of the 3 core elements (segmentation, quantitative features, and classification) are outlined, and recent literature is discussed. Although red blood cells are a significant part of this context, this study focuses on malignant lymphoid cells and blast cells. Results ...
Citation
Rodellar, J., Alferez, S., Acevedo, A., Molina, Á., Merino, A. Image processing and machine learning in the morphological analysis of blood cells. "International journal of laboratory hematology", 1 Maig 2018, vol. 40, núm. S1, p. 46-53.
Keywords
automatic cell classification, blood cells, image analysis, machine learning, morphological analysis
Group of research
CoDAlab - Control, Dynamics and Applications

Participants

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