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- Rodriguez, Alvaro, et al.
(författare)
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Refining particle positions using circular symmetry
- 2017
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Ingår i: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 12:4
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Tidskriftsartikel (refereegranskat)abstract
- Particle and object tracking is gaining attention in industrial applications and is commonly applied in: colloidal, biophysical, ecological, and micro-fluidic research. Reliable tracking information is heavily dependent on the system under study and algorithms that correctly determine particle position between images. However, in a real environmental context with the presence of noise including particular or dissolved matter in water, and low and fluctuating light conditions, many algorithms fail to obtain reliable information. We propose a new algorithm, the Circular Symmetry algorithm (C-Sym), for detecting the position of a circular particle with high accuracy and precision in noisy conditions. The algorithm takes advantage of the spatial symmetry of the particle allowing for subpixel accuracy. We compare the proposed algorithm with four different methods using both synthetic and experimental datasets. The results show that C-Sym is the most accurate and precise algorithm when tracking micro-particles in all tested conditions and it has the potential for use in applications including tracking biota in their environment.
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| 2. |
- Rodriguez, Alvaro, et al.
(författare)
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ToxId : an efficient algorithm to solve occlusions when tracking multiple animals
- 2017
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Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Video analysis of animal behaviour is widely used in fields such as ecology, ecotoxicology, and evolutionary research. However, when tracking multiple animals, occlusion and crossing are problematic, especially when the identity of each individual needs to be preserved. We present a new algorithm, ToxId, which preserves the identity of multiple animals by linking trajectory segments using their intensity histogram and Hu-moments. We verify the performance and accuracy of our algorithm using video sequences with different animals and experimental conditions. The results show that our algorithm achieves state-of-the-art accuracy using an efficient approach without the need of learning processes, complex feature maps or knowledge of the animal shape. ToxId is also computationally efficient, has low memory requirements, and operates without accessing future or past frames.
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| 3. |
- Stangner, Tim, et al.
(författare)
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Step-by-step guide to reduce spatial coherence of laser light using a rotating ground glass diffuser
- 2017
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Ingår i: Applied Optics. - : Optical Society of America. - 1559-128X .- 2155-3165. ; 56:19, s. 5427-5435
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Tidskriftsartikel (refereegranskat)abstract
- Wide field-of-view imaging of fast processes in a microscope requires high light intensities motivating the use of lasers as light sources. However, due to their long spatial coherence length, lasers are inappropriate for such applications, as they produce coherent noise and parasitic reflections, such as speckle, degrading image quality. Therefore, we provide a step-by-step guide for constructing a speckle-free and high-contrast laser illumination setup using a rotating ground glass diffuser driven by a stepper motor. The setup is easy to build, cheap, and allows a significant light throughput of 48%, which is 40% higher in comparison to a single lens collector commonly used in reported setups. This is achieved by using only one objective to collect the scattered light from the ground glass diffuser. We validate our setup in terms of image quality, speckle contrast, motor-induced vibrations, and light throughput. To highlight the latter, we record Brownian motion of micro-particles using a 100x oil immersion objective and a high-speed camera operating at 2000 Hz with a laser output power of only 22 mW. Moreover, by reducing the objective magnification to 50x, sampling rates up to 10,000 Hz are realized. To help readers with basic or advanced optics knowledge realize this setup, we provide a full component list, 3D-printing CAD files, setup protocol, and the code for running the stepper motor.
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| 4. |
- Zhang, Hanqing, et al.
(författare)
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UmUTracker : a versatile MATLAB program for automated particle tracking of 2D light microscopy or 3D digital holography data
- 2017
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Ingår i: Computer Physics Communications. - : Elsevier. - 0010-4655 .- 1879-2944. ; 219, s. 390-399
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Tidskriftsartikel (refereegranskat)abstract
- We present a versatile and fast MATLAB program (UmUTracker) that automatically detects and tracks particles by analyzing video sequences acquired by either light microscopy or digital in-line holographic microscopy. Our program detects the 2D lateral positions of particles with an algorithm based on the isosceles triangle transform, and reconstructs their 3D axial positions by a fast implementation of the Rayleigh-Sommerfeld model using a radial intensity profile. To validate the accuracy and performance of our program, we first track the 2D position of polystyrene particles using bright field and digital holographic microscopy. Second, we determine the 3D particle position by analyzing synthetic and experimentally acquired holograms. Finally, to highlight the full program features, we profile the microfluidic flow in a 100 gm high flow chamber. This result agrees with computational fluid dynamic simulations. On a regular desktop computer UmUTracker can detect, analyze, and track multiple particles at 5 frames per second for a template size of 201 x 201 in a 1024 x 1024 image. To enhance usability and to make it easy to implement new functions we used object-oriented programming. UmUTracker is suitable for studies related to: particle dynamics, cell localization, colloids and microfluidic flow measurement.Program summaryProgram title: UmUTracker Program Files doi: http://dx.doi.org/10.17632/fkprs4s6xp.1Licensing provisions: Creative Commons by 4.0 (CC by 4.0)Programming language: MATLAB Nature of problem: 3D multi-particle tracking is a common technique in physics, chemistry and biology. However, in terms of accuracy, reliable particle tracking is a challenging task since results depend on sample illumination, particle overlap, motion blur and noise from recording sensors. Additionally, the computational performance is also an issue if, for example, a computationally expensive process is executed, such as axial particle position reconstruction from digital holographic microscopy data. Versatile robust tracking programs handling these concerns and providing a powerful post-processing option are significantly limited.Solution method: UmUTracker is a multi-functional tool to extract particle positions from long video sequences acquired with either light microscopy or digital holographic microscopy. The program provides an easy-to-use graphical user interface (GUI) for both tracking and post-processing that does not require any programming skills to analyze data from particle tracking experiments. UmUTracker first conduct automatic 2D particle detection even under noisy conditions using a novel circle detector based on the isosceles triangle sampling technique with a multi-scale strategy. To reduce the computational load for 3D tracking, it uses an efficient implementation of the Rayleigh-Sommerfeld light propagation model. To analyze and visualize the data, an efficient data analysis step, which can for example show 4D flow visualization using 3D trajectories, is included. Additionally, UmUTracker is easy to modify with user customized modules due to the object-oriented programming style.Additional comments: Program obtainable from https://sourceforge.net/projects/umutracker/
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