This thesis explores the application of dynamic light scattering optical coherence tomography (DLS-OCT) for in-line particle sizing and flow measurements in particle suspensions. DLS-OCT is capable of measuring the depth-resolved particle diffusion coefficient, which can then be converted into particle size. This capability is particularly advantageous for in-line particle sizing scenarios, where the suspension is under flow, and the depth-resolved particle diffusion coefficient can be separated from the flow contribution. However, there are several other challenges associated with DLS-OCT, such as measuring: at high particle concentrations, in fast and slow flows, in multiple scattering media, and quantifying the measurement uncertainty. These challenges are addressed in this thesis.

In concentrated suspensions, the relationship between particle size and the diffusion coefficient is not well described by the simple Stokes-Einstein equation and the diffusion becomes dependent on multiple factors. Accurate determination of particle size necessitates diffusion coefficient measurements across a wide range of wavenumbers and the application of sophisticated rheological models. In Chapter 2, we address this issue with a broadband DLS-OCT system covering the wavelength range of 350–1000 nm. By inverting hard-sphere rheological models, we successfully measured the particle size and polydispersity in very dense nanoparticle suspensions. Furthermore, we demonstrated the applicability to particle sizing in suspensions that are not suitable for standard DLS-OCT measurements and showed how measurements of different diffusion modes can assess the number-based particle size polydispersity in concentrated suspensions.

DLS-OCT measurement of high flow speeds and small particle sizes in fastflowing suspensions is problematic due to detector sampling limitations, as the rapid decay of the autocorrelation function prevents the extraction of flow speed and particle size information. To address this, in Chapter 3, we showed the incorporation of beam scanning—a standard feature in many OCT systems—to extend the capabilities of DLS-OCT flow imaging beyond its current limitations and improve particle sizing in flowing suspensions. This approach allowed us to demonstrate a two-fold improvement in the flow velocity dynamic measurement range and more accurate particle size measurement deeper within the flow channel, away from the edges. These advancements are beneficial for in-line pharmaceutical and process industry particle sizing applications, where diffusion and mixing near the edges are slower, leading to overestimation of particle size.

Particle Brownian motion imposes limitations on the minimum flow speeds measurable in particle suspensions using DLS-OCT. In Chapter 4, we address this challenge by introducing the concept of number fluctuations to DLS-OCT. This innovation enabled the successful measurement of sub-diffusion flow speeds and particle concentrations in dilute particle suspensions, both in 1D and 2D. By extending the capability of DLS-OCT, this development also facilitates the measurement of the beam shape within the particle suspension, a task traditionally requiring complex calibration in conventional OCT systems.

In Chapter 5, we demonstrate the application of number-fluctuation DLS-OCT for measuring simultaneous 2D flow profiles in organ-on-chip (OoC) devices, overcoming limitations of conventional Doppler OCT and DLS-OCT in low-flow environments. A numerical method was employed to equalize axial and transverse OCT resolutions, eliminating the dependence on Doppler angles in the autocorrelation function and enabling accurate measurement of absolute flow velocities. Additionally, we implemented particle image velocimetry (PIV) on the OCT data to complement numberfluctuation measurements with precise in-plane velocity vector maps. This chapter underscores the effectiveness of number-fluctuation DLS-OCT in biomedical imaging, particularly for measuring extremely small flow speeds and addressing flow direction variability within OoC devices.

The lack of readily available theoretical models for estimating the uncertainty in DLS-OCT measurements of diffusion and flow is a challenge addressed in Chapter 6. We conducted a detailed assessment of precision and bias in DLS-OCT measurements, revealing that errors in autocorrelation coefficients are strongly correlated over time, which complicates accurate quantification of uncertainty in particle size and flow speed measurements. To address this challenge, we introduced a novel method of mixing different autocorrelation functions at the same time delay. This approach effectively eliminates error correlations and enables us to achieve precision levels approaching the Cramer-Rao lower bound. This advancement allows for reliable quantification of particle size and flow speed uncertainties using DLS-OCT, which is crucial for applications in the process industry where maximizing precision is essential.

Multiple scattering in DLS-OCT complicates accurate particle sizing as the models assume single backscattering. In Chapter 7, we propose a simple method to simulate multiple scattering effects on particles undergoing Brownian motion. Through simulations and experimental measurements, we demonstrated that the autocorrelation functions exhibit double-exponential decay in the multiple scattering regime. We employed a double-exponential autocorrelation fit model for all depths, significantly enhancing both the depth range of reliable particle sizing using the singlescattering model. In addition, we can perform particle sizing in the diffusing-wave spectroscopy (DWS) limit of the decorrelation rate.

The final Chapter 8 summarizes the key contributions of this thesis to particle sizing and flow measurements using DLS-OCT. It also discusses potential future research directions aimed at improving the accuracy and expanding the applicability of DLS-OCT across various sectors of the process industry.

Organ-on-chip (OoC) systems combine the advantages of well-characterised human cells with the benefits of engineered, physiological-like microenvironments. The extracellular matrix is the natural microenvironment of cells in the human body responsible for providing the appropriate stimuli to cells to control cell processes such as morphogenesis. OoCs can mimic the ECM, via biomaterials, fluid channels and porous membranes, to provide the cells with (patho)physiological stimuli governed by the fluid dynamics in the system. Resolving fluid behaviour in OoC systems can not only aid in fine tuning the stimuli sensed by the cultured cells and control cell fate, but also perform quantitative OoC system inspections. The current state-of-the-art methods for evaluating fluid flow in the OoC systems are simulations, theoretical calculations, and empirical observations, however a real-time quantitative characterization is lacking.
In this study, we use optical coherence tomography (OCT) for measuring both the flow in different regions of the Bi/ond inCHIPit microfluidic OoC and also simultaneously obtain structural information of the OoC system. We used a commercially available high resolution (3 microns in air) spectral domain OCT system. We made quantitative 1D and 2D flow measurements using phase-resolved Doppler-OCT and number fluctuation dynamic light scattering OCT to measure the flow under realistic use scenarios in the supply flow channels and, in the tissue supporting culture well where perfusion flow occurs. The results were compared to computational fluid dynamic simulations, and found to be in partial agreement. Moreover, we investigated the effects of fixed cells on the flow behaviour demonstrating real-time biologically relevant flow information and extended the work to qualitatively evaluate the perfusion flow in the presence of a liver sample in the culture well. The results of the study pave the way for further studies that determine the shear stress forces experienced by the cells in the OoC system.

As demand for chips increases and critical dimension keeps shrinking, the inspection of wafer becomes one of the critical challenges in the high volume production of chips. Coherent Fourier scatterometry (CFS) is a scanning bright field technique that is capable to detect nanoparticles on Si surfaces. The optical readout of CFS consists of a two pixel split detector that gives a voltage signal based on the intensity difference between the two halves. While an area of the wafer is raster scanned, the flat surface with no particles gives a zero voltage and on the particle an asymmetrical (non-zero) signal will be detected.

In this thesis, we demonstrate the use of synthetic optical holography (SOH) as a new method to improve the sensitivity of CFS. By adding a reference mirror with a piezo stage to the setup, we can interfere the scattered field with a plane reference wave. And by moving the mirror in steps, we can change the phase of the reference wave for every line of the raster scan, such that the 2D scan represents a digital off-axis hologram. Applying the standard digital holography reconstruction process, we retrieve a signal that equals the complex far field difference scaled by the reference field amplitude.

Overall, we see consistent signal-to-noise ratio (SNR) improvement over the conventional CFS. For the detection of a polystyrene latex (PSL) particle with a diameter of 60 nm (λ/10) on a silicon wafer, this new implementation leads to a SNR of 10 dB, which is about 4 dB over the filtered conventional CFS signal. For measurements of a dust particle using a very low amount of incident power (0.0014 mW on wafer), a SNR gain of more than 6 dB is achieved compared to filtered conventional CFS, due to the attenuation of low frequency electronic noises. Therefore, the implementation of SOH improves the sensitivity for detecting small nanoparticles and allows low power applications, such as biological imaging.

Disease model systems, such as the zebrafish, play an important role in understanding the onset of diseases like cancer and monitor the efficacy of new drugs. In the past, non-invasive methods for screening, diagnostics and treatment monitoring were intrinsically from the outside. In the past decades, there has been a strong drive to look inside these model systems, which resulted in the development of many small animal tomographic imaging techniques. Due to the absence of ionizing radiation, high-resolution, and cost efficiency, optical tomography is a popular imaging technique to study disease model systems such as zebrafish. The main obstacles in obtaining high-resolution imaging suitable for tissue characterization are the scattering of light in tissue and diffraction of optical waves. Scattering of light in tissue degrades the resolution of optical tomography systems, especially for thick samples. In this thesis, transmission optical coherence tomography (OCT) is used to select ballistic, non-scattered, from non-ballistic, scattered, light. We demonstrate that transmission optical coherence tomography is a versatile tool to measure optical properties of liquids, solids, and particle suspensions. The developed technique is used to perform quantitative optical tomography of the refractive index and attenuation coefficient. A good agreement is observed between our measurements and literature values for group refractive index, group velocity dispersion, and attenuation coefficient. Based on the tomographic reconstruction of transmission OCT measurements, the median attenuation coefficient, group refractive index and volumes of various organs of an adult zebrafish are segmented and quantified in optical coherence projection tomography reconstructions. In optical tomography light is imaged by a lens onto the camera. Due to the focusing of light onto the camera, this light is collected non-uniformly along the propagation direction from the sample. Consequently, the straight-ray assumption as in standard (pre-) clinical X-ray CT reconstruction is violated. Reconstruction of optical tomography images with standard filtered back projection (FBP) causes radial blurring and tangential blurring that becomes stronger with increasing distance to the rotation axis. We present 2D and 3D tomographic reconstruction algorithms that include the point spread function (PSF) of the imaging system. For emission optical projection tomography, these methods show greatly reduced radial and tangential blurring over the entire field of view 113 114 Summary and a significantly improved signal-to-noise ratio compared to FBP. The 3D PSF-based algorithm is evaluated using different initializations. When initialized with the 2D PSF-based reconstruction result, the 3D PSF-based reconstruction gives an improved signal-to-background and image quality in a useful timeframes. Besides including the physical point spread function (PSF) in the 2D tomographic reconstruction, the effect of the PSF also can be reduced by deconvolution of the FBP reconstructed image or filtering the sinogram before FBP reconstruction. We compared the performance of these techniques with each other based on simulations and the signal-to-noise ratio and the sharpness in reconstructed fluorescent beads and zebrafish OPT images. We demonstrate that the sinogram filtering performs poorly on data acquired with high numerical aperture optical imaging systems. We show that the deconvolution technique performs best for highly sparse, low signal-to-noise ratio objects. The PSF-based reconstruction method is superior for non-sparse objects and data of high signal-to-noise ratio. In this thesis, we developed novel algorithms for transmission OCT signal processing and PSF-based tomographic reconstruction. Our algorithms allow for high-resolution quantitative imaging in turbid media. These techniques can be used for quantitative optical imaging of disease model systems. Potentially this may lead to more insight in tissue development and disease onset, progression, and treatment.

Optical coherence tomography (OCT) is a technique for non-invasive imaging based on low coherence interferometry. Its main application is found in ophthalmology, where it is used for 3D in vivo imaging of the cornea and the retina. OCT has evolved over the past decade as one of the most important ancillary tests in ophthalmic practice, providing great diagnostic value for disease screening and monitoring. In retinal OCT imaging, the lateral resolution is not determined by the pupil size, but instead it is limited by optical wavefront aberrations of the cornea and lens. These aberrations reduce the OCT image resolution and lower the signal to noise ratio. To obtain high quality OCT images the optical aberrations can be removed using adaptive optics (AO).

In general, AO consists of an adaptive optical element and a wavefront sensor. The adaptive element, such as a deformable mirror, is used to reshape the wavefront and remove the undesired aberrations. The wavefront sensor measures the aberrations by reconstructing the phase of the wavefront, which is used to determine the correction on the wavefront applied by the deformable mirror. However, the use of a wavefront sensor has some disadvantages. It requires light being directed out of the imaging path onto the wavefront sensor. This leads to a loss of signal in the imaging path and can result in non-common optical path errors in the aberrations estimation procedure. Additionally, the use of a deformable mirror and a wavefront sensor leads to a bulky and expensive OCT setup.

The work presented in this thesis has the goal of reducing the cost and bulkiness of an AO-OCT system. First, we investigate the influence of optical wavefront aberrations to the OCT signal strength. The establishment of the relation between aberrations and the OCT signal strength is key to estimating and correcting the aberrations based on single OCT scans. By using Fresnel optical wave propagation and determining the fiber coupling efficiency, we find that the OCT transfer function, i.e. the function that expresses the relation between the aberrations and OCT signal strength, is quasi-convex. We determine both analytically and experimentally the transfer function for both reflective and scattering media, such as a mirror and Scotch tape sample. Additionally, if the OCT system and its optical properties are well-known we demonstrate a method to correct a defocus aberration in one step.

Second, we use the OCT transfer function to develop and determine an efficient wavefront sensorless (WFSL) AO optimization procedure. WFSL-AO methods aim to correct the aberrations without using a wavefront sensor, but instead base the determination of the wavefront on the imaging signal itself. This eliminates the use of the wavefront sensor, its extra cost and its disadvantages from an AO-OCT setup. To keep up with the OCT imaging rate, which is of the order of several tens of kHz, the algorithm has to be computationally efficient. Furthermore, there are no analytic derivatives available for the optimization and the OCT signal is very noisy. Finally, the derivative-free optimization algorithm also has to be able to determine the aberrations accurately when dealing with a minimum number of noisy measurements. We developed the Data-based Online Nonlinear extremum-seeker (DONE) algorithm. Every iteration, the DONE algorithm updates a surrogate function, which is based on random Fourier expansions (RFE) of the OCT transfer function, with a new OCT signal measurement. The optimum of the RFE surrogate function is then found with a well-known (quasi-Newton) optimization method. We demonstrate the effectiveness of the DONE algorithm compared to other optimization algorithms for WFSL-AO on biological and non-biological samples. We conclude that DONE has a smaller convergence error, while maintaining similar or faster convergence speeds compared to the other algorithms.

Third, we demonstrate a fully functional WFSL-AO OCT setup for retinal imaging. We use a state-of-the-art deformable lens with 18 actuators, rather than a deformable mirror, which leads to a smaller and more integrated WFSL-AO setup. The WFSL-AO OCT setup is successfully used for in vivo retinal OCT imaging and demonstrates that the DONE algorithm can remove the ocular wavefront aberrations with the deformable lens during in vivo OCT imaging. By developing a new algorithm and exploring the options for adaptive components, we have succeeded in retinal WFSL-AO OCT.

In a broader perspective, we show that the DONE algorithm is suitable for other applications than WFSL-AO OCT. We demonstrate that the DONE derivative-free optimization algorithm is robust towards noisy measurements for applications in robotics, microscopy and optical beam forming networks.