Toward automated and real-time 3D PTV measurements for microfluidics

The increasing use of microfluidics in industrial, biomedical, and clinical applications requires a more and more precise control of the microfluidic flows and suspended particles or cells. This leads to higher demands in three-dimensional and automated particle tracking methods, e.g. for use in feedback-control systems. In order to meet these demands, we present in this work an algorithm for performing General Defocusing Particle Tracking (GDPT) in a fast, versatile, and automated manner. GDPT is a 3D particle tracking method based on defocused particle images which is suitable for non-expert users and requires only standard laboratory equipment. The presented algorithm includes (i) an automatic identification of particles via the a priori measured reference set of particle images, (ii) a quick depth coordinate determination through a prediction of expected particle image similarities, and (iii) an iterative approach for detection of overlapping particles. We show that the algorithm is versatile and can be applied to different types of images (darkfield and brightfield) and that it is not sensitive to background or illumination fluctuations. We use synthetic image sets of varying particle concentration to evaluate the performance of the algorithm in terms of detected depth coordinate uncertainty, particle detection rate, and processing time. The algorithm is especially suitable for applications where real-time feedback control is needed and we illustrate this by using synthetic images to simulate a real-time experiment of particles undergoing acoustophoresis in a microfluidic device. The simulated experiment showed that the processing time could be significantly reduced using the presented algorithm without compromising the reliability of the detection. Our results pave the road for real-time applications of GDPT and for its improvements in processing accuracy, precision, and time.