Real time Liver-on-a-chip platform with integrated micro(bio)sensors for preclinical validation of graphene-based magnetic nanocarriers towards cancer theranostics

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Manual and automatic image analysis segmentation methods for blood flow studies in microchannels

Publication . Carvalho, Violeta Meneses; Gonçalves, Inês M.; Souza, Andrews Victor Almeida; Souza, Maria Sabrina; Bento, David; Ribeiro, J.E.; Lima, Rui A.; Pinho, Diana

In blood flow studies, image analysis plays an extremely important role to examine raw data obtained by high-speed video microscopy systems. This work shows different ways to process the images which contain various blood phenomena happening in microfluidic devices and in microcirculation. For this purpose, the current methods used for tracking red blood cells (RBCs) flowing through a glass capillary and techniques to measure the cell-free layer thickness in different kinds of microchannels will be presented. Most of the past blood flow experimental data have been collected and analysed by means of manual methods, that can be extremely reliable, but they are highly time-consuming, user-intensive, repetitive, and the results can be subjective to user-induced errors. For this reason, it is crucial to develop image analysis methods able to obtain the data automatically. Concerning automatic image analysis methods for individual RBCs tracking and to measure the well know microfluidic phenomena cell-free layer thickness, two developed methods are present and discuss in order to demonstrate their feasibility for accurate data acquisition in such studies Additionally, a comparison analysis between manual and automatic methods was performed.

2021Journal article

Open access