Automated three-dimensional tracking of living cells by digital holographic microscopy

Langehanenberg, Patrik; Ivanova, Lyubomira; Bernhardt, Ingolf; Ketelhut, Steffi; Vollmer, Angelika; Dirksen, Dieter; Georgiev, G.; Bally, Gert von; Kemper, Björn

doi:10.1117/1.3080133

Cited by 124 publications

(74 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…28 velocity. Therefore, the mean values are comparable 10 between the simulated minerals experiencing pure dissolution, precipitation, or growth and those experiencing coupled dissolution-precipitation, so the surface-normal velocity limits in Table 24 are valid for coupled dissolution-precipitation experiments as well. …”

mentioning

confidence: 78%

“…It is a quantitative phase microscopy technique capable of being configured for reflection or transmission microscopy, and it has been used for a variety of applications [1], including static and dynamic surface metrology [2][3][4][5][6][7], particle tracking [8,9], tracking and monitoring of live biological cells [3,[10][11][12], and monitoring surface dissolution [13,14] or growth [15] kinetics. DHM and related quantitative phase imaging technologies have been extensively developed for the study of biological specimens [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Phase Uncertainty in Digital Holographic Microscopy Measurements in the Presence of Solution Flow Conditions

Brand¹

2017

J. RES. NATL. INST. STAN.

View full text Add to dashboard Cite

Digital holographic microscopy (DHM) is a surface topography measurement technique with reported sub-nanometer vertical resolution. Although it has been made commercially available recently, few studies have evaluated the uncertainty or noise in the phase measurement by the DHM. As current research is using the DHM to monitor surface topography changes of dissolving materials under flowing water conditions, it is necessary to evaluate the effect of water and flow rate on the uncertainty in the measurement. Uncertainty in this study was concerned with the temporal standard deviation per pixel of the reconstructed phase. Considering the effects of solution flow rate, magnification, objective lens type (air or immersion), and experimental configuration, measurements under static conditions in air and in water with an immersion lens yielded the smallest amount of uncertainty (mean of ≤ 0.5 nm up to 40× magnification). Increasing the water flow rate resulted in an increase in mean uncertainty to ≤ 0.6 nm up to 40× with an immersion lens. Observations of a sample through a glass window at 20× magnification in flowing water also yielded increasing uncertainty, with mean values of ≤ 0.5 nm, ≤ 0.8 nm, and ≤ 1.1 nm for flow rates of 0 mL min ) did not significantly impact the uncertainty in the phase. Collecting holograms in single-wavelength versus dual-wavelength modes did impact the uncertainty, with the mean uncertainty at 10× magnification for the same wavelength being ≤ 0.5 nm from the single-wavelength mode compared to ≤ 1.5 nm from the dualwavelength mode. When the quantified uncertainty was applied to simulated dissolution data, lower limits of measured dissolution rates were found below which the measured data may not be distinguishable from the uncertainty in the measurement. The limiting surface-normal dissolution velocity is −10 −11.7 m s ) flowing water conditions in experiments with a glass window, respectively. The data presented by this study will allow for better experimental design and methodology for future dissolution or precipitation studies using DHM and will provide confidence in the data produced in postprocessing.

show abstract

mentioning

confidence: 78%

Section: Introductionmentioning

confidence: 99%

Phase Uncertainty in Digital Holographic Microscopy Measurements in the Presence of Solution Flow Conditions

Brand¹

2017

J. RES. NATL. INST. STAN.

View full text Add to dashboard Cite

show abstract

“…Both optical height and refractive index fluctuations are then used to quantify differences between biological samples [5][6][7][8][9]. DHM has been utilized in many biological applications such as determination of cellular motility [5,10], morphology [11] and biomechanics [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Automated Fourier space region-recognition filtering for off-axis digital holographic microscopy

He¹,

Nguyen²,

Pratap³

et al. 2016

Biomed. Opt. Express

View full text Add to dashboard Cite

Automated label-free quantitative imaging of biological samples can greatly benefit high throughput diseases diagnosis. Digital holographic microscopy (DHM) is a powerful quantitative label-free imaging tool that retrieves structural details of cellular samples non-invasively. In off-axis DHM, a proper spatial filtering window in Fourier space is crucial to the quality of reconstructed phase image. Here we describe a region-recognition approach that combines shape recognition with an iterative thresholding method to extracts the optimal shape of frequency components. The region recognition technique offers fully automated adaptive filtering that can operate with a variety of samples and imaging conditions. When imaging through optically scattering biological hydrogel matrix, the technique surpasses previous histogram thresholding techniques without requiring any manual intervention. Finally, we automate the extraction of the statistical difference of optical height between malaria parasite infected and uninfected red blood cells. The method described here paves way to greater autonomy in automated DHM imaging for imaging live cell in thick cell cultures.

show abstract

“…With these advantages, particle image velocimetry for flow profiling of microfluidics can be applied using the DHM technique [5,6]. DHM is also used for measuring the shape and trajectories of E. coli [7], red blood cells [8], and position tracking of many different cells types [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

UmUTracker: A versatile MATLAB program for automated particle tracking of 2D light microscopy or 3D digital holography data

Zhang

Stangner

Wiklund

et al. 2017

Computer Physics Communications

View full text Add to dashboard Cite

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 µm 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 × 201 in a 1024 × 1024 image. To enhance usability and to make it easy to implement new functions we used objectoriented programming. UmUTracker is suitable for studies related to: particle dynamics, cell localization, colloids and microfluidic flow measurement. 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. PROGRAM SUMMARY Friday, April 21, 2017Manuscript 2 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 programing style.

show abstract

Automated three-dimensional tracking of living cells by digital holographic microscopy

Cited by 124 publications

References 32 publications

Phase Uncertainty in Digital Holographic Microscopy Measurements in the Presence of Solution Flow Conditions

Phase Uncertainty in Digital Holographic Microscopy Measurements in the Presence of Solution Flow Conditions

Automated Fourier space region-recognition filtering for off-axis digital holographic microscopy

UmUTracker: A versatile MATLAB program for automated particle tracking of 2D light microscopy or 3D digital holography data

Contact Info

Product

Resources

About