Abstract
Red blood cells (RBCs) deformability is a high relevant mechanical property, whose variations are associated with some diseases, such as diabetes and malaria. Therefore, the present study aims to compare different image processing methods for assessing the RBCs deformability in a continuous flow, measured in a polydimethylsiloxane (PDMS) microchannel composed by 15 μm spacing inner pillars. The images were acquired with a high speed camera and analyzed with ImageJ software for tracking and measuring the RBCs deformation index (DI). Additionally, to understand the performance of the software, it was performed a comparison between different image processing tools provided by ImageJ and the best methods for the deformation measurements were selected, considering the measured RBCs number and their DIs. The results show that those image methods significantly affect the number of measured RBCs and their DIs and, therefore, the studies focused on the deformability measurements need to take into account the effect of the image processing methods for avoiding loss of relevant information in the images.
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Acknowledgments
This work was supported by FCT with the reference project UID/EEA/04436/2013, by FEDER funds through the COMPETE 2020 – Programa Operacional Competitividade e Internacionalização (POCI) with the reference project POCI-01- 0145-FEDER- 006941. V. Faustino, S.O. Catarino and D. Pinho thank, respectively, the FCT for the grants SFRH/BD/99696/2014, SFRH/BPD/108889/2015 and SFRH/BD/89077/2012, supported by national funds from Ministérios da Ciência, Tecnologia e Ensino Superior and by FSE through the POCH - Programa Operacional Capital Humano. The authors also acknowledge the financial support provided by the project Nos. UID/EMS/00532/2013 and UID/EMS/04077/2013.
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Faustino, V., Catarino, S.O., Pinho, D., Minas, G., Lima, R. (2018). A Comparative Study of Image Processing Methods for the Assessment of the Red Blood Cells Deformability in a Microfluidic Device. In: Tavares, J., Natal Jorge, R. (eds) VipIMAGE 2017. ECCOMAS 2017. Lecture Notes in Computational Vision and Biomechanics, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-319-68195-5_100
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DOI: https://doi.org/10.1007/978-3-319-68195-5_100
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