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Digital holography and image processing methods for applications in biophysics
Umeå University, Faculty of Science and Technology, Department of Physics. (Biophysics & Biophotonics group)
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Understanding dynamic mechanisms, morphology and behavior of bacteria are important to develop new therapeutics to cure diseases. For example, bacterial adhesion mechanisms are prerequisites for initiation of infections and for several bacterial strains this adhesion process is mediated by adhesive surface organelles, also known as fimbriae. Escherichia coli (E. coli) is a bacterium expressing fimbriae of which pathogenic strains can cause severe diseases in fluidic environments such as the urinary tract and intestine. To better understand how E. coli cells attach and remain attached to surfaces when exposed to a fluid flow using their fimbriae, experiments using microfluidic channels are important; and to assess quantitative information of the adhesion process and cellular information of morphology, location and orientation, the imaging capability of the experimental technique is vital.

In-line digital holographic microscopy (DHM) is a powerful imaging technique that can be realized around a conventional light microscope. It is a non-invasive technique without the need of staining or sectioning of the sample to be observed in vitro. DHM provides holograms containing three-dimensional (3D) intensity and phase information of cells under study with high temporal and spatial resolution. By applying image processing algorithms to the holograms, quantitative measurements can provide information of position, shape, orientation, optical thickness of the cell, as well as dynamic cell properties such as speed, growing rate, etc.

In this thesis, we aim to improve the DHM technique and develop image processing methods to track and assess cellular properties in microfluidic channels to shed light on bacterial adhesion and cell morphology. To achieve this, we implemented a DHM technique and developed image processing algorithms to provide for a robust and quantitative analysis of holograms. We improved the cell detection accuracy and efficiency in DHM holograms by developing an algorithm for detection of cell diffraction patterns. To improve the 3D detection accuracy using in-line digital holography, we developed a novel iterative algorithm that use multiple-wavelengths. We verified our algorithms using synthetic, colloidal and cell data and applied the algorithms for detecting, tracking and analysis. We demonstrated the performance when tracking bacteria with sub-micrometer accuracy and kHz temporal resolution, as well as how DHM can be used to profile a microfluidic flow using a large number of colloidal particles. We also demonstrated how the results of cell shape analysis based on image segmentation can be used to estimate the hydrodynamic force on tethered capsule-shaped cells in micro-fluidic flows near a surface.

Place, publisher, year, edition, pages
Umeå: Umeå University , 2018. , p. 59
Keywords [en]
Digital holographic microscopy, image processing, image reconstruction, bacterial adhesion, cell morphology, algorithm development, software design, quantitative measurement, microfluidics, multidisciplinary research
National Category
Biophysics Computer Vision and Robotics (Autonomous Systems)
Research subject
Signal Processing; Technical Physics
Identifiers
URN: urn:nbn:se:umu:diva-150687ISBN: 978-91-7601-915-3 (print)OAI: oai:DiVA.org:umu-150687DiVA, id: diva2:1239196
Public defence
2018-09-07, Naturvetarhuset, N430, Umeå, 13:15 (English)
Opponent
Supervisors
Available from: 2018-08-17 Created: 2018-08-15 Last updated: 2018-08-16Bibliographically approved
List of papers
1. A fast and robust circle detection method using isosceles triangles sampling
Open this publication in new window or tab >>A fast and robust circle detection method using isosceles triangles sampling
2016 (English)In: Pattern Recognition, ISSN 0031-3203, E-ISSN 1873-5142, Vol. 54, p. 218-228Article in journal (Refereed) Published
Abstract [en]

Circle detection using randomized sampling has been developed in recent years to reduce computational intensity. However, randomized sampling is sensitive to noise that can lead to reduced accuracy and false-positive candidates. To improve on the robustness of randomized circle detection under noisy conditions this paper presents a new methodology for circle detection based upon randomized isosceles triangles sampling. It is shown that the geometrical property of isosceles triangles provides a robust criterion to find relevant edge pixels which, in turn, offers an efficient means to estimate the centers and radii of circles. For best efficiency, the estimated results given by the sampling from individual connected components of the edge map were analyzed using a simple clustering approach. To further improve on the accuracy we applied a two-step refinement process using chords and linear error compensation with gradient information of the edge pixels. Extensive experiments using both synthetic and real images have been performed. The results are compared to leading state-of-the-art algorithms and it is shown that the proposed methodology has a number of advantages: it is efficient in finding circles with a low number of iterations, it has high rejection rate of false-positive circle candidates, and it has high robustness against noise. All this makes it adaptive and useful in many vision applications.

Place, publisher, year, edition, pages
Elsevier, 2016
Keywords
Circle detection, Randomized algorithm, Sampling strategy, Isosceles triangles
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Analysis
Identifiers
urn:nbn:se:umu:diva-112312 (URN)10.1016/j.patcog.2015.12.004 (DOI)000372380700017 ()
Funder
Swedish Research Council, 2013-5379
Available from: 2015-12-05 Created: 2015-12-05 Last updated: 2018-08-15Bibliographically approved
2. Detecting Bacterial Surface Organelles on Single Cells using Optical Tweezers
Open this publication in new window or tab >>Detecting Bacterial Surface Organelles on Single Cells using Optical Tweezers
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2016 (English)In: Langmuir, ISSN 0743-7463, E-ISSN 1520-5827, Vol. 32, no 18, p. 4521-4529Article in journal (Refereed) Published
Abstract [en]

Bacterial cells display a diverse array of surface organelles that are important for a range of processes such as: intercellular communication, motility and adhesion leading to biofilm formation, infections and bacterial spread. More specifically, attachment to host cells by Gram-negative bacteria are mediated by adhesion pili, which are nm wide and µm long fibrous organelles. Since these pili are significantly thinner than the wavelength of visible light, they cannot be detected using standard light microscopy techniques. At present, there is no fast and simple method available to investigate if a single cell expresses pili while keeping the cell alive for further studies. In this study, we present a method to determine the presence of pili on a single bacterium. The protocol involves imaging the bacterium to measure its size, followed by predicting the fluid drag based on its size using an analytical model, and thereafter oscillating the sample while a single bacterium is trapped by an optical tweezer to measure its effective fluid drag. Comparison between the predicted and the measured fluid drag thereby indicate the presence of pili. Herein, we verify the method using polymer coated silica microspheres and Escherichia coli bacteria expressing adhesion pili. Our protocol, can in real time and within seconds assist single cell studies by distinguishing between piliated and non-piliated bacteria.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2016
National Category
Physical Chemistry Materials Engineering
Identifiers
urn:nbn:se:umu:diva-119441 (URN)10.1021/acs.langmuir.5b03845 (DOI)000375809100015 ()27088225 (PubMedID)
Funder
Swedish Research Council, 2013-5379
Available from: 2016-04-19 Created: 2016-04-19 Last updated: 2018-08-15Bibliographically approved
3. Refining particle positions using circular symmetry
Open this publication in new window or tab >>Refining particle positions using circular symmetry
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2017 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 4, article id e0175015Article in journal (Refereed) Published
Abstract [en]

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.

National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:umu:diva-135283 (URN)10.1371/journal.pone.0175015 (DOI)000399955200030 ()
Funder
Swedish Research Council, 2013-5379
Available from: 2017-05-26 Created: 2017-05-26 Last updated: 2018-08-15Bibliographically approved
4. UmUTracker: a versatile MATLAB program for automated particle tracking of 2D light microscopy or 3D digital holography data
Open this publication in new window or tab >>UmUTracker: a versatile MATLAB program for automated particle tracking of 2D light microscopy or 3D digital holography data
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2017 (English)In: Computer Physics Communications, ISSN 0010-4655, E-ISSN 1879-2944, Vol. 219, p. 390-399Article in journal (Refereed) Published
Abstract [en]

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 summary

Program title: UmUTracker Program Files doi: http://dx.doi.org/10.17632/fkprs4s6xp.1

Licensing 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/

Place, publisher, year, edition, pages
Elsevier, 2017
Keywords
Image processing, Digital holographic microscopy, Particle tracking velocimetry, Microfluidics
National Category
Computer Vision and Robotics (Autonomous Systems) Other Physics Topics
Identifiers
urn:nbn:se:umu:diva-131047 (URN)10.1016/j.cpc.2017.05.029 (DOI)000407984100035 ()
Available from: 2017-02-03 Created: 2017-02-03 Last updated: 2018-08-15Bibliographically approved
5. Step-by-step guide to reduce spatial coherence of laser light using a rotating ground glass diffuser
Open this publication in new window or tab >>Step-by-step guide to reduce spatial coherence of laser light using a rotating ground glass diffuser
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2017 (English)In: Applied Optics, ISSN 1559-128X, E-ISSN 2155-3165, Vol. 56, no 19, p. 5427-5435Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Optical Society of America, 2017
National Category
Atom and Molecular Physics and Optics
Identifiers
urn:nbn:se:umu:diva-135625 (URN)10.1364/AO.56.005427 (DOI)000404745800041 ()
Available from: 2017-06-01 Created: 2017-06-01 Last updated: 2018-08-15Bibliographically approved
6. 3D printed water-soluble scaffolds for rapid production of PDMS micro-fluidic flow chambers
Open this publication in new window or tab >>3D printed water-soluble scaffolds for rapid production of PDMS micro-fluidic flow chambers
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2018 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 8, no 1, article id 3372Article in journal (Refereed) Published
Abstract [en]

We report a novel method for fabrication of three-dimensional (3D) biocompatible micro-fluidic flow chambers in polydimethylsiloxane (PDMS) by 3D-printing water-soluble polyvinyl alcohol (PVA) filaments as master scaffolds. The scaffolds are first embedded in the PDMS and later residue-free dissolved in water leaving an inscription of the scaffolds in the hardened PDMS. We demonstrate the strength of our method using a regular, cheap 3D printer, and evaluate the inscription process and the channels micro-fluidic properties using image analysis and digital holographic microscopy. Furthermore, we provide a protocol that allows for direct printing on coverslips and we show that flow chambers with a channel cross section down to 40 x 300 μm can be realized within 60 min. These flow channels are perfectly transparent, biocompatible and can be used for microscopic applications without further treatment. Our proposed protocols facilitate an easy, fast and adaptable production of micro-fluidic channel designs that are cost-effective, do not require specialized training and can be used for a variety of cell and bacterial assays. To help readers reproduce our micro-fluidic devices, we provide: full preparation protocols, 3D-printing CAD files for channel scaffolds and our custom-made molding device, 3D printer build-plate leveling instructions, and G-code.

Place, publisher, year, edition, pages
Nature Publishing Group, 2018
National Category
Other Materials Engineering Other Engineering and Technologies not elsewhere specified Other Physics Topics
Identifiers
urn:nbn:se:umu:diva-144631 (URN)10.1038/s41598-018-21638-w (DOI)000425500300044 ()
Funder
Swedish Research Council, 2013-5379The Kempe Foundations, JCK-1622
Available from: 2018-02-08 Created: 2018-02-08 Last updated: 2018-08-16Bibliographically approved
7. A drag force interpolation model for capsule-shaped cells in fluid flows near a surface
Open this publication in new window or tab >>A drag force interpolation model for capsule-shaped cells in fluid flows near a surface
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2018 (English)In: Microbiology, ISSN 1350-0872, E-ISSN 1465-2080, Vol. 164, no 4, p. 483-494Article in journal (Refereed) Published
Abstract [en]

We report an interpolation model to calculate the hydrodynamic force on tethered capsule-shaped cells in micro-fluidic flows near a surface. Our model is based on numerical solutions of the full Navier–Stokes equations for capsule-shaped objects considering their geometry, aspect ratio and orientation with respect to fluid flow. The model reproduced the results from computational fluid dynamic simulations, with an average error of <0.15 % for objects with an aspect ratio up to 5, and the model exactly reproduced the Goldman approximation of spherical objects close to a surface. We estimated the hydrodynamic force imposed on tethered Escherichia coli cells using the interpolation model and approximate models found in the literature, for example, one that assumes that E. coli is ellipsoid shaped. We fitted the 2D-projected area of a capsule and ellipsoid to segmented E. coli cells. We found that even though an ellipsoidal shape is a reasonable approximation of the cell shape, the capsule gives 4.4 % better agreement, a small difference that corresponds to 15 % difference in hydrodynamic force. In addition, we showed that the new interpolation model provides a significantly better agreement compared to estimates from commonly used models and that it can be used as a fast and accurate substitute for complex and computationally heavy fluid dynamic simulations. This is useful when performing bacterial adhesion experiments in parallel-plate flow channels. We include a MATLAB script that can track cells in a video time-series and estimate the hydrodynamic force using our interpolation formula.

Place, publisher, year, edition, pages
Microbiology Society, 2018
Keywords
E. coli, adhesion, Goldman’s approximation, tethered cells, micro-fluidics
National Category
Other Physics Topics Other Biological Topics
Research subject
Physics
Identifiers
urn:nbn:se:umu:diva-144499 (URN)10.1099/mic.0.000624 (DOI)29509130 (PubMedID)2-s2.0-85045149561 (Scopus ID)
Available from: 2018-02-05 Created: 2018-02-05 Last updated: 2018-08-16Bibliographically approved
8. Object plane detection and phase retrieval from single-shot holograms using multi-wavelength in-line holography
Open this publication in new window or tab >>Object plane detection and phase retrieval from single-shot holograms using multi-wavelength in-line holography
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Phase retrieval and the twin-image problem in digital in-line holographic microscopy can be resolvedby iterative reconstruction routines. However, recovering the phase properties of an object in a hologramneeds an object plane to be chosen correctly for reconstruction. In this work, we present a novelmulti-wavelength Gerchberg-Saxton algorithm to determine the object plane using single-shot hologramsrecorded with multiple wavelengths in an in-line holographic microscope. For micro-sized objects, weverify the object positioning capabilities of the method for various shapes and derive the phase informationusing synthetic and experimental data. Experimentally, we built a compact digital in-line holographicmicroscopy setup around a standard optical microscope with a regular RGB-CCD camera andacquire holograms of micro-spheres, E. coli and red blood cells, that are illuminated using three lasersoperating at 491nm, 532nm and 633nm, respectively. We demonstrate that our method provides accurateobject plane detection and phase retrieval under noisy conditions, e.g., using low-contrast hologramswithout background normalization. This method allows for automatic positioning and phase retrievalsuitable for holographic particle velocimetry, and object tracking in biophysical or colloidal research.

Keywords
digital holographic microscopy, image reconstruction, multiple wavelengths
National Category
Biophysics
Research subject
Physics
Identifiers
urn:nbn:se:umu:diva-150685 (URN)
Available from: 2018-08-15 Created: 2018-08-15 Last updated: 2018-08-15
9. DSeg: a dynamic image segmentation program to extract backbone patterns for filamentous bacteria and hyphae structures
Open this publication in new window or tab >>DSeg: a dynamic image segmentation program to extract backbone patterns for filamentous bacteria and hyphae structures
Show others...
2019 (English)In: Microscopy and Microanalysis, ISSN 1431-9276, E-ISSN 1435-8115, Vol. 25, no 3, p. 711-719Article in journal (Refereed) Published
Abstract [en]

Analysis of numerous filamentous structures in an image is often limited by the ability of algorithms to accurately segment complex structures or structures within a dense population. It is even more problematic if these structures continuously grow when recording a time-series of images. To overcome these issues we present DSeg; an image analysis program designed to process time-series image data, as well as single images, to segment filamentous structures. The program includes a robust binary level-set algorithm modified to use size constraints, edge intensity, and past information. We verify our algorithms using synthetic data, differential interference contrast images of filamentous prokaryotes, and transmission electron microscopy images of bacterial adhesion fimbriae. DSeg includes automatic segmentation, tools for analysis, and drift correction, and outputs statistical data such as persistence length, growth rate, and growth direction. The program is available at Sourceforge.

Place, publisher, year, edition, pages
Cambridge University Press, 2019
Keywords
filamentous, hyphae, image segmentation, MATLAB, software, quantitative measurement
National Category
Biophysics
Research subject
Computerized Image Analysis; cell research
Identifiers
urn:nbn:se:umu:diva-150686 (URN)10.1017/S1431927619000308 (DOI)000474798800016 ()30894244 (PubMedID)
Note

Originally included in thesis in manuscript form.

The program is available at https://sourceforge.net/projects/dseg-software

Available from: 2018-08-15 Created: 2018-08-15 Last updated: 2019-08-07Bibliographically approved

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