It is hypothesized that the uncertainty of the Synchrony® model from the rotation of a geometrically asymmetrical single fiducial shall be non-zero during the motion tracking. To validate this hypothesis, the uncertainty was measured for a Synchrony® model built for a respiratory motion phantom oriented at different yaw angles on a Cyberknife® treatment table. A Mini-ball Cube with three cylindrical GoldMark™ (1mmx5mm Au) numbered fiducials was placed inside a respiratory phantom and used for all tests. The fiducial with the least artifact interference was selected for the motion tracking. A 2cm periodic, longitudinal, linear motion of the Mini-ball cube was executed and tested for yaw rotational angles, 0° – 90°. The test was repeated over 3 nonconsecutive days. The uncertainty increased with the yaw angle with the most noticeable changes seen between20° and 60° yaw, where uncertainty increased from 23.5% to 57.9%. A similar test was performed using a spherical Gold Anchor™ fiducial. The uncertainties found when using the Gold Anchor™ were statistically lower than those found when using the GoldMark™ fiducial for all angles of rotation. For the first time, it is found that Synchrony® model uncertainty depends on fiducial geometry. In addition, this research has shown that tracking target rotation using a single fiducial can be accomplished with the Synchrony® model uncertainty as it is displayed on the treatment console. The results of this research could lead to decreased acute toxicity effects related to multiple fiducials. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection

Harbours play a vital role in the economies of most countries since a significant amount of international trade is conducted through them. Ships rely on harbours for the safe loading and unloading of cargo and the harbour infrastructure relies on breakwaters for protection. As a result, the design and analysis of breakwaters receives keen interest from the engineering community. Coastal engineers need an easy-to-use tool that can model the way in which waves interact with large numbers of interlocking armour units. Although the study of fluid–structure interaction generates a lot of research activity, none of the reviewed literature describes a suitable method of analysis. The goal of the research was to develop a simulation algorithm that meets all the criteria by allowing CFD software and physics middleware to work in unison. The proposed simulation algorithm used Linux “shell scripts” to coordinate the actions of commercial CFD software (Star-CCM+) and freely available physics middleware (PhysX). The CFD software modelled the two-phase fluid and provided force and moment data to the physics middleware so that the movement of the armour units could be determined. The simulation algorithm was verified numerically and experimentally. The numerical verification exercise was of limited value due to unresolved issues with the CFD software chosen for the analysis, but it was shown that PhysX responds appropriately given the correct force data as input. Experiments were conducted in a hydraulics laboratory to study the interaction of a solitary wave and cubes stacked on a platform. Fiducial markers were used to track the movement of the cubes. The phenomenon of interest was the transfer of momentum from the wave to the rigid bodies, and the results confirmed that the effect was captured adequately. The study concludes with suggestions for further study. / MIng (Mechanical Engineering), North-West University, Potchefstroom Campus, 2014

Harbours play a vital role in the economies of most countries since a significant amount of international trade is conducted through them. Ships rely on harbours for the safe loading and unloading of cargo and the harbour infrastructure relies on breakwaters for protection. As a result, the design and analysis of breakwaters receives keen interest from the engineering community. Coastal engineers need an easy-to-use tool that can model the way in which waves interact with large numbers of interlocking armour units. Although the study of fluid–structure interaction generates a lot of research activity, none of the reviewed literature describes a suitable method of analysis. The goal of the research was to develop a simulation algorithm that meets all the criteria by allowing CFD software and physics middleware to work in unison. The proposed simulation algorithm used Linux “shell scripts” to coordinate the actions of commercial CFD software (Star-CCM+) and freely available physics middleware (PhysX). The CFD software modelled the two-phase fluid and provided force and moment data to the physics middleware so that the movement of the armour units could be determined. The simulation algorithm was verified numerically and experimentally. The numerical verification exercise was of limited value due to unresolved issues with the CFD software chosen for the analysis, but it was shown that PhysX responds appropriately given the correct force data as input. Experiments were conducted in a hydraulics laboratory to study the interaction of a solitary wave and cubes stacked on a platform. Fiducial markers were used to track the movement of the cubes. The phenomenon of interest was the transfer of momentum from the wave to the rigid bodies, and the results confirmed that the effect was captured adequately. The study concludes with suggestions for further study. / MIng (Mechanical Engineering), North-West University, Potchefstroom Campus, 2014

Quantifying human posture and range of motion remains challenging due to the need for specific technologies, time for data collection and analysis, and space requirements. The demand for affordable and accessible human body position measurement requires alternative methods that cost less, are portable, and provide similar accuracy to expensive multi-camera systems. This thesis developed and evaluated a novel augmented reality mobile app for human posture measurement to bring marker-based body segment measurement to the point of patient contact. The augmented reality app provides live video of the person being measured, AprilTag2 fiducial markers locations in the video, processes marker data, and calculates angles and distances between markers. Results demonstrated that the mobile app can identify, track, and measure angles and distances between AprilTag2 markers attached to a human body in real-time with millimetre accuracy, thereby allowing researchers and clinicians to quantify posture measurements anywhere, at anytime.

This thesis contributes to the topic of image-based feature localization and tracking in fluoroscopic (2D x-ray) image sequences. Such tracking is needed to automatically measure organ motion in cancer patients treated with radiation therapy. While the use of 3D cone-beam computed tomography (CBCT) images is a standard clinical practice for verifying the agreement of the patient's position to a plan, it is done before the treatment procedure. Hence, measurement of the motion during the procedure could improve plan design and the accuracy of treatment delivery. Using an existing CBCT imaging system is one way of collecting fluoroscopic sequences for such analysis. Since x-ray images of soft tissues are typically characterized with low contrast and high noise, radio-opaque fiducial markers are often inserted in or around the target. This thesis describes techniques that comprise a complete system for automated detection and tracking of the markers in fluoroscopic image sequences. One of the cornerstone design ideas in this thesis is the use of the 3D CBCT image of the patient, from which the markers can be extracted more easily, to initialize the tracking in the fluoroscopic image sequences. To do this, a specific marker-based image registration framework was proposed. It includes multiple novel techniques, such as marker segmentation and modelling, the marker enhancement filter, and marker-specific template image generation approaches. Through extensive experiments on testing data sets, these novel techniques were combined with appropriate state-of-the-art methods to produce a sleek, computationally efficient, fully automated system that achieved reliable marker localization and tracking. The accuracy of the system is sufficient for clinical implementation. The thesis demonstrates an application of the system to the images of prostate cancer patients, and includes examples of statistical analysis of organ motion that can be used to improve treatment planning. / Dissertation / Doctor of Philosophy (PhD) / This thesis presents the development of a software system that analyzes sequences of 2D x-ray images to automatically measure organ motion in patients undergoing radiation therapy for cancer treatment. The knowledge of motion statistics obtained from this system creates opportunities for patient-specific treatment design that may lead to a better outcome. Automated processing of organ motion is challenging due to the low contrast and high noise levels in the x-ray images. To achieve reliable detection, the proposed system was designed to make use of 3D cone-beam computed tomography images of the patient, where the features (markers) are easier to identify. This required the development of a specific image registration framework for aligning the images, including a number of novel feature modelling and image processing techniques. The proposed motion tracking approach was implemented as a complete software system that was extensively validated on phantom and patient studies. It achieved a level of accuracy and reliability that is suitable for clinical implementation.

Radiation therapy has a significant role in the management of cancer patients. Computed tomography (CT) has been at the forefront of radiation therapy planning due to its widespread diagnostic use and its electron density information. Magnetic resonance (MR) imaging is another proven diagnostic modality, which can achieve superior soft tissue contrast and margin delineation, relative to CT. As such it has become a valuable tool for cancer diagnoses and staging. In this study, a centre-out radial acquisition using an off-resonance reception (co-RASOR) MR sequence, sensitive to magnetic field inhomogeneity, was applied to excite a broader frequency range of spins in the vicinity of metallic seeds. The resultant images display local hyperintensities around metallic markers. These images were then reconstructed with frequency offsets to rewind these hyperintensities to the geometric centre to obtain positive contrast. The contrast-to-noise ratio (CNR) was measured between a fiducial and its surrounding to compare Fourier and iterative reconstruction methods for undersampled co-RASOR. The motivation was to reduce the sequence acquisition time, while preserving sufficient CNR and resolution. For single slices, acquisition was 2.8 sec and multi-slice acquisition could acquire more than 50 slices in 73 sec, by reducing the acquired data by a factor of 8. This effectively encodes acquisition to 1.4 sec/slice. The noise present in undersampled images decreased significantly using iterative reconstruction methods, but a total variation based penalty better preserved the edges. Further extensions to the reconstruction method applied frequency-based filters that could isolate signals from different metallic compounds. The local hyperintensities rewind using opposite signed frequency offsets for diamagnetic and paramagnetic seeds. This allowed individual visualization of a low dose rate (LDR) brachytherapy seed and a gold fiducial marker. Phantom validation showed that each seed contains its maximal CNR in opposing frequency regions. The relative difference between global and local maxima in each frequency band ranged from 1.19 -- 3.73, and a single cut-off frequency was successfully applied for each acquisition plane. Image guidance systems rely on the position of these fiducial markers to compare daily setup images with CT and MR simulations. Phantom experiments and porcine tissue samples were used to assess the minimum separation of fiducials, geometric accuracy, and random errors associated with using the co-RASOR sequence. co-RASOR images were able to resolve fiducials separated by 0.5 - 1 cm, depending on image resolution. No systematic biases were observed by comparing co-RASOR to CT using rigid body registrations. The standard deviation of the systematic errors were \textless 0.5 mm between MR and CT registrations, and \textless 0.4 mm between MR scans without CT. These values are smaller than the current total systematic uncertainties, which should be limimed to <3 mm. The methods presented here can aid in understanding the trade-offs between acquisition speed and signal properties, differentiating cases where brachytherapy seeds are used in combination with fiducial markers for external beam boost, and aid in co-registration of multimodality imaging. / Thesis / Doctor of Philosophy (PhD)

Stereopsis or Stereo vision is a technique that has been extensively used in computer vision these days helps to percept the 3D structure and distance of a scene from two images taken at different viewpoints, precisely the same way a human being visualizes anything using both eyes. The research involves object matching by extracting features from images and includes some preliminary tasks like camera calibration, correspondence and reconstruction of images taken by a stereo vision unit and 3D construction of an object. The main goal of this research work is to estimate the position and the orientation of a front loader bucket of an autonomous mobile robot configured in a work machine name 'Avant', which consists a stereo vision unit and several other sensors and is designed for outdoor operations like excavation. Several image features finding algorithms, including the most prominent two, SIFT and SURF has been considered for the image matching and object recognition. Both algorithms find interest points in an image in different ways which apparently accelerates the feature extraction procedure, but still the time requires for matching in both cases is left as an important issue to be resolved. As the machine requires to do some loading and unloading tasks, dust and other particles could be a major obstacle for recognizing the bucket at workspace, also it has been observed that the hydraulic arm and other equipment comes inside the FOV of the cameras which also makes the task much challenging. The concept of using markers has been considered as a solution to these problems. Moreover, the outdoor environment is very different from indoor environment and object matching is far more challenging due to some factors like light, shadows, environment, etc. that change the features inside a scene very rapidly. Although the work focuses on position and orientation estimation, optimum utilization of stereo vision like environment perception or ground modeling can be an interesting avenue of future research / <p>Validerat; 20101230 (ysko)</p>

Le cancer de la prostate est le cancer le plus fréquent chez l'homme en Europe, néanmoins il n'existe actuellement pas de technique d'imagerie permettant de détecter avec précision les tumeurs dans la glande. Sachant que les coupes histologiques contiennent la réalité de terrain concernant le diagnostic, il est nécessaire de recaler les images de chaque technique d'imagerie aux coupes histologiques afin de pouvoir les évaluer. De plus, comme il n'existe pas de méthode permettant de contrôler précisément le plan de coupe histologique, le recalage doit être considéré comme un problème 3D. Un dispositif permettant de réaliser, de manière rapide et standardisée, des marqueurs internes dans les coupes histologiques a été développé, de même qu'un algorithme permettant de détecter automatiquement ces marqueurs, de les identifier et d'aligner les coupes histologiques. La méthode a été testée sur 10 prostates, avec en moyenne 19.2 coupes par prostate, et a permis d'obtenir une précision de recalage moyenne de 0.18 ± 0.13 mm au niveau des marqueurs. Un deuxième algorithme a été développé pour recaler les coupes histologiques, une fois alignées, avec les images IRM. Ce recalage a été conçu pour être guidé par les canaux éjaculateurs, un repère anatomique présent dans chaque prostate et visible à la fois en histologie et dans les images IRM cliniques, acquises avec une résolution standard. L'algorithme a d'abord été testé en s'appuyant sur les marqueurs artificiels. La précision obtenue pour le recalage était en moyenne de 0.45±0.25 mm au niveau des marqueurs et de 1.04 ± 0.21 mm au niveau des canaux éjaculateurs. L'algorithme a enfin été testé en guidant le recalage à l'aide de la position des canaux éjaculateurs. La précision moyenne obtenue était alors de 0.16±0.05 mm au niveau des canaux éjaculateurs et de 2.82±0.41 mm au niveau des marqueurs. Ces résultats suggèrent une valeur du facteur de rétrécissement de l'ordre de 1.07±0.03 et une inclinaison vis à vis du plan de coupe histologique de l'ordre de 13.6◦ ± 9.61◦, avec une variance importante pour ces deux paramètres / Prostate cancer is the most frequently diagnosed cancer of men in Europe, yet no current imaging technique is capable of detecting with precision tumours in the prostate. The histology slices are the gold standard for the diagnosis. Therefore, in order to evaluate each imaging technique, the histology slices must be precisely registered to the imaged data. As it cannot be assumed that the histology slices are cut along the same plane as the imaged data is acquired, the registration must be considered as a 3D problem. An apparatus has been developed that enables internal fiducial markers to be created in the histology slices in a rapid and standardised manner. An algorithm has been developed that automatically detects and identifies these markers, enabling the alignment of the histology slices. The method has been tested on 10 prostate specimens, with 19.2 slices on average per specimen. The accuracy of the alignment at the fiducial markers was on average 0.18±0.13 mm. A second algorithm was developed to 3D register the aligned histology slices with the MR images. The registration is designed to be guided by the ejaculatory ducts, an anatomical landmark present in every prostate and visible in both histology and MR images acquired at standard clinical resolution. The algorithm was first tested by using the fiducial needles to guide the registration. The average registration accuracy was 0.45 ± 0.25 mm at the fiducial needles and 1.04±0.21 mm at the ejaculatory ducts. The algorithm was then tested by using the ejaculatory ducts to guide the registration. The average registration accuracy was 0.16±0.05 mm at the ejaculatory ducts and 2.82 ± 0.41 mm at the fiducial needles. The results suggest that the histology shrinkage factor is of the order 1.07±0.03 and the tilt of the histology slicing plane is 13.6◦ ±9.61◦, with both parameters showing significant variance

Mobile virtual reality (VR) headsets have been becoming more and more popular. However, the cheapest headsets do not come with any controllers and the ones that do include controllers only uses sensors for rotation, not translational movement. This thesis project aims to develop a prototype of a Bluetooth connected controller for the mobile VR headsets. The controller is based on a MetamotionC board produced by mbientlab Inc., which comes with Bluetooth Low Energy (BLE), an ARM M4 microcontroller, an miniature inertial measurement unit (IMU) sensor (containing a 3-axis accelerometer, a 3-axis gyroscope, and a 3-axis magnetometer and a barometer), a thermometer and other sensors. The only sensors used in this project are the accelerometer, gyroscope, and magnetometer. As a finished prototype, the MetaMotionC is placed on a glove together with five Aruco markers; a 3D model of a hand intended to use as an avatar of the glove was made with Blender and MakeHuman; and a VR room to use the controller with was created in Unity. The 3D hand responds to rotational and translational movements via Bluetooth connection to the IMU sensor on the MetaMotionC. The smartphone camera is used to detect the glove's position with Aruco markers, and the 3D hand is moved to a corresponding location in the VR room. The OpenCV library is used for image processing. The sensor data is filtered with low-pass, median, and thresholding to improve the measurement accuracy. Zero velocity update is used to reset the drift of the integrated accelerations. To reduce the integration error, Romberg's method with a floating window is implemented in Matlab. However, it did not reduce the error enough to make a difference. Thus, the result was unreliable.

Multicopters such as quadcopters are a popular tool within industries such as mining, shipping and surveillance where a high level of autonomy can save time, increase efficiency and most importantly provide safety. While Unmanned Aerial Vehicles have been a big area in research and used in the mentioned industries, the level of autonomy is still low. Simple actions such as loading and offloading payload or swapping batteries is still a manual task performed by humans. If multicopters are to be used as an autonomous tool the need for solutions where the machines can perform the simplest task such as swapping batteries become an important stepping stone to reach the autonomy goals. Earlier works propose landing solutions focused on landing autonomous vehicles but the lack of accuracy is hindering the vehicles to safely dock with a landing platform. This thesis combines multiple areas such as trajectory generation, visual marker tracking and UAV control where results are shown in both simulation and laboratory experiments. With the use of a Model Predictive Controller for both trajectory generation and UAV control, a multicopter can safely land on a small enough platform which can be mounted on a small mobile robot. Additionally an algorithm to tune the trajectory generator is presented which shows how much weights can be increased in the MPC controller for the system to remain stable.