KEYWORDS: Particles, Optical tracking, Field programmable gate arrays, Detection and tracking algorithms, CMOS sensors, High speed cameras, Video processing, Video acceleration, Video, Time metrology
Measuring the mechanical properties of living tissue is a challenging task due to the small sizes and the fragility of the living organisms. A promising method, which works best on small scales, is the passive microrheology, which observes the motion of tracing beads within the sample. The video imaging method observes this motion by imaging the tracer particles with suitable optics (e.g. a microscope). As living tissue is a complex material, the viscoelastic properties are highly frequency dependent; therefore, a fast high-speed camera is needed to resolve the important frequencies in the 100 to 1000 Hz regime. As the data rate of high-speed cameras exceed the storage speed, only short burst of measurements can be carried out. This leads to a limited dynamic range of frequencies and missed measurement opportunities. It normally is not possible to track all the particles in real time to avoid the storage requirement of the video, as the tracking needs to be very precise and thus has a high computing demand.
In this presentation, a combination of a CMOS imaging sensor with an FPGA is presented, which, in combination, allows for virtually unlimited long high-speed tracking of up to eight particles at up to 10 kHz. First, the sensor and the FPGA combinations are laid out. Secondly, the used particle tracking algorithm and its implementation is explained and benchmarked with a known state-of-the-art algorithm. Finally, this integrated sensor solution is mounted on a standard microscope and hour long tracking experiments on living 3T3 fibroblasts are carried out, studying the impact of blebbistatin on the mobility of polystyrene beads within the cell.
KEYWORDS: Microfluidics, Particles, Cameras, Field programmable gate arrays, Imaging systems, Optical analysis, Particle systems, High speed cameras, Sensors, Control systems
Nowadays, high-speed video microscopy is used in many applications like microrheology1, 2 or flow cytometry3 to measure mechanical properties of cells or to identify their type. Typically, high-speed cameras use buffering to reach very high frame rates due to the limited bandwidth of the interface to a PC like Ethernet or USB. Additionally, analysis of large data is compute-intense and in many cases difficult to do online. We developed a system that consists of a high speed CMOS image sensor combined with a field programmable gate array (FPGA) and a pulsed LED illumination system. Due to an image transformation that is done on the FPGA, the dimensionality of the data is reduced without loss of important information. This leads to a significant reduction of the amount of data as well as to noise reduction as a side effect. Furthermore, we developed a modular analysis toolkit that can be used to do the whole analysis directly on the same FPGA online so that buffering is not required and measurements can run continuously on high frame rates. Hence, we can analyze a large total number of objects at very high throughput rates in microfluidic devices. We present the analysis of diluted whole blood in a microfluidic system with our device as well as a sorting application that uses multiple regions of interest that are observed simultaneously so that particles can be analyzed before and after a manipulation or gate.
The mechanical properties of cells are important parameters in medicine and natural science. In this work we present a new setup that is capable of stretching adherent cells with light. For the first time, the mechanical properties of adherent cells can be determine with an active method without influencing the results by interaction of a probe or having to alter the biochemistry of the cells (e.g. by applying trypsin to detach them from the substrate). Additionally, a method to detect the resulting deformation has been developed as well as the necessary data analysis algorithms. To quantify and compare the deformation, data are fitted to viscoelastic models consisting of differently connected networks of springs and dashpods. The Akaike information criterion is used to select the best models. With the determined parameters, the mechanical properties can be assessed and 3T3 fibroblasts measured as cultured are compared to latrunculin treated ones. Regarding all parameters, the new technique delivers results in the expected range with respect to the overall mechanical properties of the cells. Furthermore, by investigating the behavior of individual parameters, also conclusions about different timescales can be drawn and the interplay of parts of the cytoskeleton during mechanical deformation is resolved. In addition, the new, active stretching technique proved to be more accurate and sensitive than the well established technique of passive microrheology.
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