Deformable Mirror (DM) is the key part in the AO system. Characterization of DM is important as it maps between input voltage signal and output mirror deformation. The precision of characterization largely affects the control performance. While characterizing the DM with wavefront sensors is easy and straightforward, there is very few research on the characterizing the DM in a Wavefront sensorless (WFSless) setup. Existing research focuses on using Phase Diversity Phase Retrieval (PDPR) methods to retrieve phase, while introducing diversity phase by using various additional hardware.

This thesis tries to use PDPR methods to characterize the DM in a WFSless setup without using any additional hardware. Diversity phase are introduced by the DM itself and calibrated afterwards. Simulation results show that the proposed method is capable of characterizing the DM. Experiments on the setup are also conducted and further validates the proposed method, while unstable setup is accountable for the undesired results of the characterization.

Future industrial lithography machines will use interferometers for wafer-stage position metrology. Interferometers suffer from phase wrapping, which is why in this thesis an absolute phase detection system has been developed. The absolute phase detection system will use two lasers, with the second laser allowing for limited changes in the wavelength. An efficient implementation of the excess fractions method has been developed to perform the absolute phase capture. To improve the longevity of the system the second laser should ideally be allowed to turn of when not used for absolute phase capture, which requires a wavelength estimation algorithm. Such a wavelength estimation algorithm has been implemented, and it can also provide an initial estimate for the OPD of the interferometer to be used in the excess fraction method. Both the excess fractions method and the wavelength estimation method have been experimentally verified. The results were satisfactory, thus providing all the building block for an absolute phase capture system.

Retrieving actionable information from large datasets is increasingly computationally expensive due to the current trend of ever-increasing dataset sizes. Reducing dataset sizes with dimensionality reduction techniques is often necessary for statistical analysis techniques, such as classification, to be computationally feasible. Most dimensionality reduction methods do not require any additional information to accomplish their task. However, datasets used for classification, for example, are accompanied by a set of class-labels as well. This extra information can improve dimensionality reduction techniques by explicitly preserving features that explain differences between classes. A field where high-dimensional and large datasets are standard is Imaging Mass Spectrometry (IMS), a technique that simultaneously records the abundance and spatial location of molecules throughout biological tissue samples. Classification has been applied to IMS datasets for a wide range of scenarios, including the diagnosis of disease, distinguishing between tumour types for personalized treatment, and identifying biomarkers. A recently introduced dimensionality reduction method called Soft Discriminant Map (SDM), designed to incorporate class information and prevent overfitting when used on high-dimensional datasets, is a promising candidate to reduce the size and dimensionality of IMS datasets. However, SDM currently requires manual setting of a free parameter β that influences class separation in the newly constructed feature-space. This thesis explores the use of SDM on IMS datasets in classification use cases and proposes a framework to set β in a data-driven way: Data-Driven Soft Discriminant Map (DD-SDM). Furthermore, the sensitivity of the classification performance to changes in β is examined. DD-SDM is compared to similar state-of-the-art dimensionality reduction methods in terms of classification performance. The performed experiments show that DD-SDM successfully finds a value for β where the classification performance is on par with, or in some scenarios better than, state-of-the-art dimensionality reduction methods while using fewer features. Setting β either too low or too high results in a suboptimal feature space and worsens classification performance. Golden section search, the search strategy used to find the optimal β in DD-SDM, succeeds in finding the optimal β in fewer iterations than more naive methods. With the use of an artificial dataset in combination with a novel evaluation metric, the Peak Conservation Score (PCS), the distinctive ability of DD-SDM to discard features that are common between classes and to actively select for discriminative features is demonstrated. The DD-SDM framework is furthermore applied to real-world IMS measurements of rat brain and mouse kidney tissue.

Introduction: Atherosclerosis, the major source of cardiovascular diseases, is one of the leading causes of death. During atherosclerosis the arterial wall is affected by a complex process of lipid driven inflammation that leads to thickening of the arterial wall resulting in a so called plaque. Because of plaque growth, the lumen of the artery gradually narrows. As the lumen area is decreasing, reduction and even restriction of blood flow can occur, which can lead to a heart attack or stroke depending on the affected artery. Biomechanical stresses are known to influence the development of the disease. Those stress are the plaque structural stress (PSS) and wall shear stress (WSS) induced by the blood flow at the vessel wall. The aim of this project was to study the contribution of these biomechanical stresses and their combination to plaque progression in human coronary arteries. In order to investigate this effect a new methodology for the calculation of the stresses was introduced that utilizes the image modalities optical coherence tomography (OCT) and intravascular ultrasound (IVUS). The combination of those two image modalities can provide more accurate information regarding the plaque composition than the approaches that have been applied so far. In particular the cap thickness, which is the region shielding the lipid rich necrotic core from the blood flow, is crucial for structural stress calculations. Methods: The new methodology consisted of three steps. During the first step image data from the image modalities optical coherence tomography (OCT) and intravascular ultrasound (IVUS) were fused. The resulted images were cross-sections of the human coronary arteries that consisted of the lumen and the outer wall obtained from IVUS and the fibrous cap obtained from OCT. However, they did not contain information about the size of the necrotic core; thus, the second step was to reconstruct the necrotic core. For that purpose an algorithm from the literature was implemented that can reconstruct the necrotic core. The produced geometry resulting from the second step consisted of the same features as those from step one but they also included the contours of the necrotic core. The third step was the calculation of the PSS using those 2D geometries. The WSS data were obtained from another study. For the statistical analysis the data of both stress calculations were ranked as low, medium and high. Two different approaches for the definition of the thresholds of those ranks were used, vessel specific and absolute thresholds. In the vessel specific approach the thresholds of the aforementioned ranks were specific for each vessel, while in the second approach the threshold values were based on the whole sample size. Those two approaches were studied in order to explore if the response of the vessels depends to the absolute values of biomechanical stresses or it is relative to their respective biomechanical stresses. Change in wall thickness was used as metric to quantify the plaque progression. In order to study the contribution of the biomechanical stresses to the plaque progression in the human coronary arteries, statistical analysis was carried out using ANOVA with plaque progression as dependent variable and PSS and WSS as independent variables. Results: Plaque development was significantly related to WSS using both approaches to rank the WSS values into low, mid and high. In general, regions exposed to low WSS showed the most plaque progression. The individual effect of PSS was not statistically significant using both approaches, however there was a trend demonstrating that high PSS could promote plaque development. When PSS and WSS were combined using the vessel specific approach to rank the data, there was plaque progression for the cases of low WSS combined with any level of plaque structural stress. However, only WSS had a statistically significant effect in this case revealing that the resulted effect was entirely estimated by WSS. If absolute thresholds were used for both WSS and PSS, there was no statistical effect. Despite that, there was a trend showing that high PSS combined with high WSS could promote plaque development. Conclusions: During this project a new methodology was utilized in order to study the contribution of WSS, PSS and their combination to the plaque development in human coronary arteries. It was also the first study that utilized the combination of the image modalities OCT and IVUS in that topic. It was demonstrated that WSS could promote plaque development. PSS also enhanced plaque progression but with no statistically significant effect. Regarding the combination, it was demonstrated that the effect was explained completely by wall shear stress for the vessel specific approach. For the absolute thresholds approach, there was no statistically significant effect. However, more data are required to validate these results.

Scanning mirror is a widely used device in many optical systems to position reflected beam. Existing products include galvanometer and resonant scanner. They are intended for accurate positioning at low frequency range and fast scanning at the specified high frequency respectively. However, when a wide frequency range is involved, they might not be able to fulfill the requirement. To solve this generic issue, Hittech starts to research new alternatives. In this paper, a novel solution is proposed, by tuning resonant frequency and exciting higher order modes to cover the intended frequency range 500 - 5k Hz. A flexure mechanism is designed, where the scanner contains a cantilever as resonator, and a cut-leafspring as hinge guiding to achieve 1 DoF resonant scan. Resonant frequency is tuned by clamping different positions of the cantilever by two surfaces with large radius of curvature, and sliding could be enabled by DLC coating. Concept and detailed design are evaluated by finite element modelling and a prototype is built. The test results show a good match with the simulation. The intended frequency range could be covered and the reflected beam could achieve a scanning angle of 1mrad. Unwanted motions of mirror are verified and limited within requirement with large margins, and hence could be negligible for operation.

The average worldwide internet traffic demand in 2022 is projected to be over 1200 Terabits per second. A fifth of this data would be transmitted using mobile networks. One of the technologies used for this is radio frequency (RF) telecommunication, but this technology is reaching its limits. Despite ongoing development, typical data rates are still in the order of Gigabits per second per link.

TNO is working on a telecommunication link (called TOmCAT) that can reach data transfer rates of a Terabit per second. The high data rate is achieved using a very promising alternative to RF telecommunication: optical telecommunication, which is also known as laser communication.

In order to reach the intended data rates, the data needs to be spread over multiple optical frequencies. These signals need to be combined into one transmitted beam using a free-space optical bulk multiplexer.

The laser beams that are transmitted by their collimators need to be aligned with respect to each other in order to reach the satellite as one beam. The footprint available for the required alignment mechanisms is very limited. Furthermore, the system needs to achieve a good thermal and mechanical stability in order to meet the strict specifications.

The aim of this thesis is two-fold: to show the need for achieving state-of-the-art alignment specifications with strict footprint constraints, and to defend the steps taken to achieve these requirements. The research spans the entire design process of the alignment assembly: from higher/system level trade-offs and calculations, to the derivation of the design specifications, to the conceptual and detailed design, and concluding with the manufacturing and testing of the first prototype.

The application of actively controlled micrometer precision positioning stages in products that are accessible to start-ups, individual consumers or third world countries is currently limited by their price and size. To solve this problem, the use of low-cost and compact components in stages is investigated. Earlier research done in the MSD group already showed that relatively low-cost sensor concepts and mechanical designs can be applied to significantly reduce the price of stages, while still achieving sub-micrometer precision. In this research, the applicability of the Arduino Due micro-controller (€40) and amplifiers based on Pulse Width Modulation (PWM, €6) in precision stages is investigated. The use of
cheap components doesn’t come without its drawbacks. To name a few examples, the Analog-to-Digital Converter (ADC) in the Arduino doesn’t have the resolution of higher quality components, PWM adds frequency content to the output of the amplifier and the Arduino processor isn’t as fast. In this research project, an extensive theoretical analysis is done to reveal how the components affect the overall performance of the stage, which can then be used to optimize system parameters to circumvent the performance losses that are inevitable with cheap components. This way much of the overall system performance can
be maintained. The theory is experimentally validated and the Arduino and PWM based amplifiers are successfully implemented into a working prototype with a precision of 1.5μm.

This study focuses on automated malaria diagnosis in low quality blood smear images, captured by a low-cost smartphone based microscope system. The aim is to localize and classify the healthy and infected erythrocytes (red blood cells) in order to evaluate the parasitaemia in an infected blood smear. Due to the lower quality of the smartphone microscope system compared to traditional high-end light microscopes, conventional algorithms fail to process these images. We propose a framework using a convolutional neural network as a pixel classifier to localize the erythrocytes. Afterwards we classify them accordingly, using a convolutional neural network as an object classifier. Such a system can offer in the-field malaria diagnosis without human intervention or can act as an aid for human experts to lower workload and increase diagnosis accuracy. The algorithm successfully localizes the erythrocytes with an average sensitivity of 97.31% and precision of 92.21%. Classification performed inadequate, in terms of low agreement with two human experts. This can be due to the low image quality or the small amount of training data available at the time.

In optical imaging, image quality is not only determined by the system itself but also by the media in which light traverse. Differences in the refraction index of the media encountered by a light wavefront produces phase aberrations which distort the image received from the original object. Currently, there are two main approaches for solving this problem: adaptive optics, which rely on deformable mirrors and wavefront sensors for correcting the phase aberration before it reaches the imaging sensor; and post-processing techniques, which try to estimate the object after receiving distorted images.

MFBD methods are a family of algorithms that are capable of reconstructing the object by fusing the information carried by a set of differently aberrated images. These techniques are widely used in current optical systems, allowing a notable increase in image quality in most situations. However, there are cases in which they are not applicable; for example, looking at a dynamic object (e.g., a bird flying) or looking through static aberrations (e.g., in microscopy applications); but certain modifications in the optical system can be used for solving this problem.

Actual optical devices have only one aperture, thus creating one full-size image on the imaging sensor but, by segmenting the pupil, several images can be retrieved at the same time with different aberrations (i.e., light follows a distinct path for each aperture). However, using a multi-aperture system implies that there is less imaging sensor area available for each aperture, thus obtaining images with less resolution. Nonetheless, MFBD algorithms can usually be extended in order to support SR, a technique that allows the increase of the object resolution by retrieving extra information from the displacement between images.

This thesis is focused on the development of a functional prototype of a multi-aperture optical system that can do real-time object reconstruction. As a MFBD technique is needed, the novel TIP algorithm (developed at Delft Center for Systems and Control) is selected. In order to achieve a fast and reliable reconstruction, the algorithm is: modified for increasing its robustness against noise, expanded in order to support SR and implemented efficiently in both CPU and GPU. Finally, the system is tested in a real environment, showing promising results.

For wavefront reconstruction, often the combination of a Shack-Hartmann sensor and a reconstruction method utilizing the Cartesian derivatives of Zernike polynomials (the least-squares method) is used, which is known to introduce cross-talk. In Janssen (2014) a new wavefront reconstruction algorithm is introduced to be used with the Shack-Hartmann sensor that does not present cross-talk. To our knowledge, this method has never been demonstrated. In the current research, Janssen's method and the conventional least-squares method are compared on a modified Michelson interferometer setup with a spatial light modulator to first remove the aberrations of the complete system, and subsequently introduce specific aberrations for which the Zernike coefficients are reconstructed using both reconstruction methods. It is found that both methods work equally well with optimal fitting powers. When fitting fewer than the optimal amount of fitting powers, it was found that Janssen's method accurately recovered Zernike coeficient amn when n + 1 powers are fit, while the conventional method achieves the same accuracy only at n + 2 fitting powers, especially when aberrations introducing cross-talk are present. When more than the optimal amount Zernike powers are used, it is seen that Janssen's method presents aliasing at lower fitting powers. At the optimal fitting power, the RMS landscape for both methods is shown to be similar, and therefore they are equally susceptible to errors due to mis- estimation of the center position and radius of the beam on the ShackHartmann
sensor. Lastly, it is shown that theoretically, Janssen's method is at least 3.5 times slower than the conventional least-squares method due to the use of complex valued Zernike polynomials.

To meet the growing demand for high precision measurement equipment, sensors with sub-nanometer resolution are becoming readily available. Because of its high precision, traceability and ease of use, the interferometer stands out for high precision measurements. However, the laser beam of an interferometer can be influenced by temperature and pressure fluctuations. Compensation of this error is possible by sensing temperature and pressure fluctuations while performing interferometric measurements. Alternatively, a refractometer running parallel with the interferometer can be used to do the same compensation with a higher accuracy. Additionally, errors caused by external sources such as vibrations, can be compensated by adopting a highly symmetrical design. Picodrift interferometer was developed and upgraded at VSL (Dutch Metrology Institute) as a calibration facility for high-precision sensors. First, the improved design of the picodrift interferometer is evaluated, implemented and tested allowing for a controlled measurement environment and high stability. The design requirements are determined to reduce the uncertainty caused by temperature and pressure fluctuations to picometer level in one hour. Based on those requirements, a vacuum system is implemented and tested to reach a pressure level in the ultra-high vacuum regime. During the implementation, necessary experiments and tests are performed to find leakages and the reasons for an undesired beam drift related to the pressure change. Additionally, an active temperature control system with passive shield is installed. Also, various kinematic coupling mount systems are designed and manufactured to provide a good positioning stability even in a noisy environment caused by a turbo pump. As the number of the interferometer channels has been doubled to perform measurements in both vacuum and atmospheric conditions, a well planned alignment procedure is developed to align the more sophisticated optical path. To characterize the performance of the new interferometer, a dead path measurement is performed. Second, to take advantage of the high precision and traceability, the interferometer is expanded to work as a calibration facility for external sensors of different sizes. A stable symmetrical calibration setup is designed to fit in a limited space for external measurements while minimizing uncertainty caused by temperature fluctuation and misalignment. An alignment procedure for the setup is developed. Eventually an example calibration is performed.