Cell counting and velocity algorithms for hydrodynamic study of unsteady biological flows in micro-channels.
Federica TorrisiGiovanna StellaFrancesca M GuarinoAnd Maide BucoloPublished in: Biomicrofluidics (2023)
In this paper, the combination of two algorithms, a cell counting algorithm and a velocity algorithm based on a Digital Particle Image Velocimetry (DPIV) method, is presented to study the collective behavior of micro-particles in response to hydrodynamic stimuli. A wide experimental campaign was conducted using micro-particles of different natures and diameters (from 5 to 16 μ m ), such as living cells and silica beads. The biological fluids were injected at the inlet of a micro-channel with an external oscillating flow, and the process was monitored in an investigated area, simultaneously, through a CCD camera and a photo-detector. The proposed data analysis procedure is based on the DPIV-based algorithm to extrapolate the micro-particles velocities and a custom counting algorithm to obtain the instantaneous micro-particles number. The counting algorithm was easily integrated with the DPIV-based algorithm, to automatically run the analysis to different videos and to post-process the results in time and frequency domain. The performed experiments highlight the difference in the micro-particles hydrodynamic responses to external stimuli and the possibility to associate them with the micro-particles physical properties. Furthermore, in order to overcome the hardware and software requirements for the development of a real-time approach, it was also investigated the possibility to detect the flows by photo-detector signals as an alternative to camera acquisition. The photo-detector signals were compared with the velocity trends as a proof of concept for further simplification and speed-up of the data acquisition and analysis. The algorithm flexibility underlines the potential of the proposed methodology to be suitable for real-time detection in embedded systems.
Keyphrases
- machine learning
- deep learning
- data analysis
- living cells
- artificial intelligence
- convolutional neural network
- neural network
- big data
- stem cells
- blood flow
- computed tomography
- minimally invasive
- magnetic resonance imaging
- mass spectrometry
- single molecule
- magnetic resonance
- mesenchymal stem cells
- high speed
- climate change
- human health