In this thesis a novel approach in generating 3D IGP is applied using shape grammar, an effective pattern generation method. The particular emphasis here is to generate the motifs (repeat unit) in 3D using parameterization, which can then be manipulated within 3D space to construct architectural structures. Three unique distinctive shape grammar algorithms were developed in 3D; Parameterized Shape Grammar (PSG), Auto-Parameterized Shape Grammar (APSG) and Volumetric Shell Shape Grammar (VSSG). Firstly, the PSG generates the motifs in 3D. It allows one to use a single changeable regular 3D polygon, and forms a motif by given grammar rules including, Euclidean transformations and Boolean operations. Next, APSG was used to construct the architectural structures that manipulates the motif by automating the grammar rules. The APSG forms a wall, a column, a self-similarity star and a dome, the main features of Islamic architecture. However, applying Euclidean transformations to create non-Euclidean surfaces resulted in gaps and or overlaps which does not form a perfect tessellation. This is improved upon by the VSSM, which integrates two key methods, shell mapping and coherent point drift, to map an aesthetically accurate 3D IGM on a given surface. This work has successfully presented methods for creating complex intricate 3D Islamic Geometric Motifs (IGM), and provided an efficient mapping technique to form visually appealing decorated structures. / Partially funded by the Centre of Visual Computing (CVC)

Advances of magnetic resonance imaging (MRI) techniques enable visualguidance to identify the anatomical target of interest during the image guidedintervention(IGI). Non-rigid image registration is one of the crucial techniques,aligning the target tissue with the MRI preoperative image volumes. As thegrowing demand for the real-time interaction in IGI, time used for intraoperativeregistration is increasingly important. This work implements 3D diffeomorphicdemons algorithm on Nvidia GeForce GTX 1070 GPU in C++ based on CUDA8.0.61 programming environment, using which the average registration time hasaccelerated to 5s. We have also extensively evaluated GPU accelerated 3D diffeomorphicregistration against both CPU implementation and Matlab codes, and theresults show that GPU implementation performs a much better algorithm efficiency.

Multimodal image registration is essential when combining functional and structural imaging modalities. Among the most common combinations, numerous methods have been developed for co-registration of CT and PET, typically validated on human size scanners. However, only a few registration studies have been performed for the combination of small animal miniPET and microCT imaging. The Jonasson Center for Medical Imaging at KTH possesses an integrated miniPET/ microCT for pre-clinical research purposes. The motivation for this work is the need for the development of fusion method(s) for combining the data of these two modalities. In this work, a novel pipeline registration method, employing image processing and Mutual Information (MI) is proposed and implemented. The method starts with a pre-alignment step before acquisition of the miniPET/microCT volumes, followed by scaling, binarization and processing of the two volumes and finally, a registration procedure by Maximization of Mutual Information (MIM) as a voxel-based similarity metric. A established intrinsic landmarks based method is also implemented for comparison. For the validation of the methods, volumes acquired by in-house designed 3D printed Polyethylene (PE) phantoms, filled with multiple concentrations of FDG were used. The misalignment between corresponding points volumes after registration, is analyzed and compared in terms of absolute spatial distance. The proposed method based on 3D processed volumes outperformed the Landmarks based registration method, showing average misalignments of 0.5 mm. The registered volumes were also successfully visualized together using Alpha blending. By so, an automatic fusion method for miniPET/microCT has thus been implemented, presented and evaluated, raising prospects for multimodal imaging research at the Jonasson Center for Medical Imaging. / Kombinationen av funktionell och strukturell avbildning är vanlig inom medicinsk bildgivning, och koregistrering av bildvolymerna utgör en essentiell del i den multimodala framställningen. PET/CT-avbildning hör till de vanligast förekommande multimodala avbildningskombinationerna, och till följd av detta har ett antal koregistreringsmetoder utvecklats för just detta. Vad gäller pre-klinisk avbildning är dock validerade koregisteringsmetoder inte lika vanliga, och framförallt inom forskningsbaserad avbildning (där egendesignade scanners förekommer) är behovet av effektiva metoder tydligt. Inom Jonassons centrum för medicinsk avbildning på KTH har ett multimodalt miniPET/ microCT-system utvecklats, och det är just behovet av koregistering som utgjort basen för följande examensarbete. I följande arbete har en koregistreringsmetod baserad på fördefinierad bildbehandling och analys av gemensam information (mutual information, MI) implementerats och testats. Metoden bygger på ett initialt upplinjeringssteg innan microCT/ miniPET bildtagning. Efter detta genomförs en rad bildbehandlingssteg (skalning, binärisering) innan en slutgiltig koregistrering genomförs med hjälp av s.k. maximering av gemensam information (Maximization of Mutual Information, MIM). En etablerad landmärkesbaserad metod implementerades även som jämförelse. Metoderna testades sedan genom multimodal avbildning av egendesignade 3D-printade fantomer, fyllda med varierande aktivitet av FDG. Den föreslagna MI-metoden överträffade den etablerade landmärkesmetoden, med ett genomsnittligt koregistreringsfel på 0.5 mm. Visualisering av de koregistrerade volymerna genomfördes även genom så kallad alpha blending. Genom detta har en koregistreringsmetod för miniPET/microCT:n på Jonassons center för medicinsk avbildning implementerats och testats, vilket möjliggör för framtida studier av multimodal avbilning på KTH.

Nationella riktlinjer finns dokumenterade i en handbok utgiven av Sveriges kommuner och landsting. I denna handbok finns de hygienregler beskrivna som ska gälla på våra operationsavdelningar. Syftet med studien är att kartlägga vilka hygienregler som gäller inom region Skånes nio opererande sjukhus och om det finns någon vetenskaplig evidens bakom dessa regler. Metoden som har använts är en empirisk intervju med kvantitativ inriktning utifrån 17 halvstrukturerade frågor. Respondenterna var elva avdelningschefer/hygienansvarig på operationsavdelningar i region Skåne. Intervjuerna genomfördes via telefon.Resultatet visar att alla operationsavdelningar har egna styrande dokument/PM angående hygienregler. Gemensamt för alla avdelningar är att de har lika kläder, använder mössor, har regler för att vit knäppt rock används vid ärende utanför operationsavdelning samt att hygiensköterskan har en rådgivande funktion på alla sjukhus. Det som skiljer sig markant mellan avdelningarna är reglerna för smycken, munskydd, klädförvaring och postoperativ infektionsregistrering. Då det inte finns några tydliga nationell/regionala hygienregler eller någon vetenskaplig evidens som styrker dessa, blir slutsatsen därför, att varje operationsavdelning tolkar hygienreglerna godtyckligt. Detta visar sig tydligt i de stora variationerna på svaren från intervjuerna. Postoperativ infektionsregistrering och gemensamma hygienregler för hela region Skånes/Sveriges operationsavdelningar bör vara en självklarhet inom svensk sjukvård. / National hygiene guidelines are documented in a handbook written by Swedens municipality and country council. In this handbook there are special hygiene rules for the operating theatre. The aim of this study was to map out the hygiene rules in operating theatre at nine hospitals in Skåne, and to find out if the rules are based on evidence. The method used was an empiric quantitative interview with seventeen semistructed questions. The respondents were eleven head nurses/hygiene responsible at the operating theatre at nine hospitals in Skåne. The interviews were accomplished by the telephone. The result shows that all operating theatres have different version with regulations of hygiene rules. In common for all were that personnel were wearing the same type of green clothes, all personal use head cover, and when they have to leave the operating theatre in some errand they wear a white-buttoned coat over the green clothes. The rules for jewellers, facemask, clothes keeping and the registration of postoperative infections differ between the hospitals. As long as there is no evident national hygiene regulation with scientific evidence that proves the outcome, it seems to be free rendering. Registration of postoperative infection and common evident hygiene rules should be self-evident in all Skånes/Swedens operating theatre in the future.

A large number of image registration techniques have been developed for various types of sensors and applications, with the aim to improve the accuracy, computational complexity, generality, and robustness. They can be broadly classified into two categories: intensity-based and feature-based methods. The primary drawback of the intensity-based approaches is that it may fail unless the two images are misaligned by a moderate difference in scale, rotation, and translation. In addition, intensity-based methods lack the robustness in the presence of non-spatial distortions due to different imaging conditions between images. In this dissertation, the image registration is formulated as a two-stage hybrid approach combining both an initial matching and a final matching in a coarse-to-fine manner. In the proposed hybrid framework, the initial matching algorithm is applied at the coarsest scale of images, where the approximate transformation parameters could be first estimated. Subsequently, the robust gradient-based estimation algorithm is incorporated into the proposed hybrid approach using a multi-resolution scheme. Several novel and effective initial matching algorithms have been proposed for the first stage. The variations of the intensity characteristics between images may be large and non-uniform because of non-spatial distortions. Therefore, in order to effectively incorporate the gradient-based robust estimation into our proposed framework, one of the fundamental questions should be addressed: what is a good image representation to work with using gradient-based robust estimation under non-spatial distortions. With the initial matching algorithms applied at the highest level of decomposition, the proposed hybrid approach exhibits superior range of convergence. The gradient-based algorithms in the second stage yield a robust solution that precisely registers images with sub-pixel accuracy. A hierarchical iterative searching further enhances the convergence range and rate. The simulation results demonstrated that the proposed techniques provide significant benefits to the performance of image registration.

Four contrasting recitals were presented to fulfill the requirements for the degree Doctor of Musical Arts. The first recital contained music of miscellaneous composers. Two Preludes and Fugues by the North German Baroque composers Vincent Libeck and Dietrich Buxtehude were separated by Samuel Scheidt's Variations on the Netherlands folk song "Ach du feiner Reiter". The Brahms Chorale Prelude "0 wie selig seid ihr doch, ihr Frommen" and the Louis Vierne "Intermezzo" from the Third Symphony represented Romantic-style composition. The major work of the program was the Carl Nielsen Commotio, a large work in orchestral style. The second recital consisted completely of music by J. S. Bach. Four works of contrasting styles were presented: Concerto, Opus 3, No. 8, composed by Antonio Vivaldi and transcribed by Bach, Partita on Sie gegrisset, Jesu gtig, Sonata IV, and Fantasy and Fugue in G Minor. The third recital was the lecture recital: Registration of Orchestral Textures in Organ Music. This lecture was an attempt to deal with the contemporary problem in performance practice of registration of Romantic organ music. The trends in organ building in the twentieth century have ranged from a deeper exploration of the possibilities of the Romantic organ to the reevaluation of and rededication to principles of organ building popular in the seventeenth and eighteenth centuries.

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.

America's Sex Offense statutes and cases are some of the most controversial sections of modern law, both for the extreme sensitivity of their subject matter as well as the scope and application of those laws. This thesis is an analysis and overview of both the objective and subjective issues posed by the current state of those very laws: the subjective portion explored the development of current laws and the diverse attendant legal issues such as over-broadness and excessive or misdirected effect as compared to the Legislative and public intent which directly led to the development of these laws. Additionally a more objective study of their efficacy was conducted through the use of data regarding offense rates by locality. This objective data was procured from both the United States Census and Bureau of Justice statistics, which contained national averages such as the overall violent crime rate, and from the Florida Department of Law Enforcement Statistics and was supplemented with additional data from other academic sources. It is both the subjective conclusion and the interpretation of objective data that while the rate of sex offenses has lowered in recent decades this effect is a part of the overall trend of reduction in all violent offenses, and that the extreme stance of modern sex offense laws have arguably resulted in the net-negative of creating a class of individuals ostracized from all but other sex offenders who are virtually incapable of supporting themselves or at times of even finding legal habitation post-release. With little to no chance of a productive life, there is the strong possibility of recidivism and little incentive to avoid re-offending.

For autonomous vehicles, 3D, rotating LiDAR sensors are critically important towards the vehicle's ability to sense its environment. Generally, these sensors scan their environment, using multiple laser beams to gather information about the range and the intensity of the reflection from an object. For multi--LiDAR systems, the placement of the sensors determines the density of the combined point cloud. I perform preliminary research on the optimal LiDAR placement strategy for an off--road, autonomous vehicle known as the Halo project. I use simulation to generate large amounts of labeled LiDAR data that can be used to train and evaluate a neural network used to process LiDAR data in the vehicle. The performance metrics of the network are then used to generalize the performance of the sensor pose. I also, describe and evaluate intrinsic and extrinsic calibration methods that are applied in the multi--LiDAR system.

Algorithms for automatic image registration and mosaicking are developed for a miniature Unmanned Aerial Vehicle (MINI-UAV) platform, assembled by Air-O-Space International (AOSI) L.L.C.. Three cameras onboard this MINI-UAV platform acquire images in a single frame simultaneously at green (550nm), red (650 nm), and near infrared (820nm) wavelengths, but with shifting and rotational misalignment. The area-based method is employed in the developed algorithms for control point detection, which is applicable when no prominent feature details are present in image scenes. Because the three images to be registered have different spectral characteristics, region of interest determination and control point selection are the two key steps that ensure the quality of control points. Affine transformation is adopted for spatial transformation, followed by bilinear interpolation for image resampling. Mosaicking is conducted between adjacent frames after three-band co-registration. Pre-introducing the rotation makes the area-based method feasible when the rotational misalignment cannot be ignored. The algorithms are tested on three image sets collected at Stennis Space Center, Greenwood, and Oswalt in Mississippi. Manual evaluation confirms the effectiveness of the developed algorithms. The codes are converted into a software package, which is executable under the Microsoft Windows environment of personal computer platforms without the requirement of MATLAB or other special software support for commercial-off-the-shelf (COTS) product. The near real-time decision-making support is achievable with final data after its installation into the ground control station. The final products are color-infrared (CIR) composite and normalized difference vegetation index (NDVI) images, which are used in agriculture, forestry, and environmental monitoring.