Fig. 1 Identification of single particles.
Fig.2 Once identified, the algorithm tracks each particle’s motion.
At CCM ELECTRONIC ENGINEERING, they develop a method to distinguish nanoparticles from images taken in darkfield microscopy. The aim is to detect the particles’ speed and determine their size according to the Brownian motion model. Ricky Jacobsen describes the procedure for us.
Particles are prefiltered and, for example, in a microfluidic chip guided to a microscope that takes darkfield images. The images clearly show particles, but it is not possible to determine the size directly.
At CCM, Ricky develops an algorithm to track the motion of single particles. The first step reduces the background in the images electronically to be able to follow single particles. The second step tracks the particles, considering proximity and similarity between particles in two images (Fig. 1 and Fig. 2).
This particle tracking is particularly challenging because the particles are very similar, and pattern recognition does not work. Ricky needs to determine suitable parameters for selecting the right particles. Once the tracking has a hit, the algorithm can determine the particle speed. Using Brownian Motion theory, one can subsequently determine the particle size. To achieve the required detection accuracy, the algorithm needs to process many images, increasing the necessary amount of stored and handled data.