Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (leaves 100).

Ultrasound imaging plays an important role in biomedical diagnostics due its safety, noninvasive nature, and low cost. Conventional ultrasound systems typically form an image frame by scanning the region of interest line-by-line, using a focused beam during transmission and dynamic focusing during reception. Alternatively, the region of interest can be insonified at once using a plane wave, which allows for ultrafast data acquisition rates but reduces the resulting image quality. The latter can be improved by means of coherent plane-wave compounding (CPWC), whereby multiple plane waves are emitted at different angles to obtain multiple image datasets that are subsequently combined to enhance the final compounded image. We present two novel Fourier-domain techniques for CPWC image reconstruction from raw linear-array sensor data. In particular, we show how to modify two classic algorithms used for geophysical data processing, namely Stolt's and slant-stack depth migration under zero-offset constant-velocity assumptions, so that their new versions become applicable to plane-wave ultrasound data processing. To demonstrate the merits and limitations of our approach, we provide qualitative and quantitative comparisons with other Fourier-domain methods reported in the ultrasound literature. Our evaluation results are based on the image resolution, contrast, and similarity metrics obtained for several public-domain experimental benchmark datasets. We also describe another novel Fourier-domain method for CPWC image reconstruction that can be used in situations where the speed of sound varies with depth in a layered propagation medium. Our technique builds on Gazdag's phase-shift migration algorithm that has been modified to handle plane-wave ultrasound data processing. Our simulation results show that the proposed method is capable of accurately imaging point targets in a three-layer medium, mimicking tissue-bone-tissue ultrasound propagation. / Graduate

Joint movements are essential for the function of human body during the activities of daily living and sports. The movement of human joints varies from normal to those which have an increased range of joint movement (gymnasts) to those with extreme disabling laxity in patients with a connective tissue disorder (Ehlers Danlos Syndrome). “Hypermobility" is most commonly used to describe excessive movement. Hypermobility was assessed by using the current criteria of the Beighton score for signs and the Brighton criteria for symptoms of hypermobility in a group of orthopaedic patients attending the specialist knee and shoulder injury clinics. The Beighton score was found to be higher in patients attending for primary ACL reconstruction (mean 2.9, p = 0.002) and revision ACL reconstruction (mean 4, p < 0.001) when compared with the control group. Hypermobility was a risk factor for the failure of ACL reconstruction (30% vs 0%). The mean Beighton score was higher in both the primary shoulder dislocation group (mean difference 1.8, p=0.001) and the recurrent shoulder dislocation group (mean difference 1.4, p=0.004). Bone defects were studied on the CT scan following shoulder dislocations. There was no correlation between hypermobility and the bone defects. The bone defect was a risk factor for recurrent shoulder instability (48% vs 16%). A material testing system was used to assess the tissue laxity of discarded hamstring tendon and shoulder capsule obtained during stabilisation procedures. The mean gradient of slope for both tendon and capsule graphs was 23.8 (range 3.08-52.63). The tissue laxity was compared to the Beighton score, however no correlation was detected between the Beighton score and the gradient of the tissue laxity. An electronic goniometer was used to measure the angle of the MCP joint of the little finger, whilst a force plate system simultaneously measured the force required to hyperextend the MCP joint. The little finger MCP joints of each hand were assessed in this manner in a group of patients undergoing primary ACL reconstruction or open shoulder stabilization. The mean force required to produce the 40 degrees angle at the little finger MCP joint was 0.04 kg with a range from 0-0.11 kg. There was a positive correlation between the gradient of tissue laxity and the force required to produce 40 degrees angle at the little finger of the dominant hand. The expression of Collagen V and Small leucine rich proteoglycans (Decorin and Biglycan) was studied in the skin, hamstring tendon and shoulder capsule of the patients described above attending with shoulder or knee instability. These patients had different levels of hypermobility (as assessed by the Beighton score) and symptoms of hypermobility (as assessed by the Brighton criteria to diagnose Benign Joint Hypermobility Syndrome). The weaker tendon group was found to have a lower mean Beighton score, while the weaker skin group had a higher mean Beighton score. Collagen V expression was higher in the skin dermal papillae of the weaker group. The Beighton Scores were higher in patients with ACL and shoulder injuries. Hypermobility was a risk factor for the failure of ACL reconstruction. There was no correlation between hypermobility and the bone defects on the CT scan following shoulder dislocation. Bone defects were a risk factor for recurrence. There was no correlation between the Beighton Score and the tissue laxity. There was a correlation between the tissue laxity and the clinical assessment of laxity at the little finger MCPJ by using a force- goniometer system. There was a correlation between the collagen V expression in the dermal papillae of the skin and the Beighton score.

Cultural adaptations to environment can result in certain biological changes in individuals (Kennedy, 1989; Jurmain, 1999). Some of these changes can affect the human skeleton and leave markers pointing to patterns of habitual behavior or general level of workload stress placed on the body. This study assesses the variation in workload caused by environmental and cultural differences of three contemporaneous Nubian groups of the Kerma era (2,500-1,500BC) in ancient Nubia. The skeletal samples used here are from three contemporaneous ancient Nubian groups who lived during this period. The Kerma Collection represents a population from the urban capital city of Kerma in Upper Nubia (1,750-1,500BC; n=216), the collection of the Northern Dongola Reach Survey (NDRS) represents a rural population located 70km south of the Kerma city in Upper Nubia (2,500-1,750BC; n=48), and the C-Group collection represents a subsistence based society from the area of Lower Nubia (2,000-1,600BC; n=109). The rural and urban groups were located in the fertile area of Sudan known as the Dongola Reach and the subsistence based society occupied the more rugged, desert-like terrain outside of the Dongola Reach. Behavioral reconstruction markers entheseal changes (EC), workload trauma, and degenerative joint disease (DJD) were employed in order to attain broader answers of how Homo sapiens from the same civilization cope with varying environments. Results suggest that the subsistence based population (C-Group) experienced the least amount of workload stress, suggesting increase in workload with an increase in agricultural intensity/social complexity, as both the urban and rural populations had much more intensive agriculture and were more socially complex than the subsistence based population. This increase in workload with the advent of agriculture (Cohen and Armelagos, 1984; Goodman et al., 1984; Larsen, 1995) and with increase in social complexity (Zabecki, 2009) has been suggested in prior studies with other populations and this is seen here. Furthermore, though sex differences concerning pattern of behavior are clearer in the C-Group suggesting fewer habitual activities due to a less complex society (as suggested by Petersen, 1998; Eshed et al., 2004), similar behavior differences between sexes were still somewhat visible in the urban and rural populations. This suggests that some cultural traits remain constant in the Nubian culture despite environment or level of social complexity. The Kerma city and NDRS collections are, in general, highly stressed when compared to the C-Group or contemporaneous populations, irrespective of which marker is assessed. This may be due to the intensive agriculture practiced or the threat of attack from other populations forcing strenuous construction and fortification efforts of settlements. Juvenile remains, which are traditionally excluded from behavior studies, displayed lesions on several areas of the skeleton which may suggest heavy workload. This study builds on previous information known about the people of the Kerma era and gains a clearer perspective of how these populations lived their lives from day to day. These data can be used to continue investigation into ways in which environment and culture affect human biology and, in turn, the human skeleton.

Cette thèse avance que le cas de la Sierra Leone est édifiant pour comprendre le paradoxe de l'effondrement et de la reconstruction des Etats africains néo-patrimoniaux dans l'ère post-Guerre Froide. Il vise à identifier les processus historiques, politiques et sociaux spécifiques qui ont mené à l'effondrement de l'Etat en Sierra Leone, mais aussi les dynamiques à l'oeuvre dans sa reconstruction. Elle s'appuie sur l"hypothèse selon laquelle l'effondrement et la reconstruction de l'Etat révèlent des continuités de la formation de l'Etat en Sierra Leone. / This thesis advance the argument that the case of Sierra Leone is exemplary for understanding the collapse of and reconstruction of neo-patrimonial states in Africa after the end of the cold war. It identifies the historical and socio-political processes that led to the collapse of the state but also the dynamics of its reconstruction. It is based on the hypothesis that state collapse and reconstruction underlines the continuities of state formation processes.

Image recovery and segmentation are always the fundamental tasks in image processing field, because of their so many contributions in practical applications. As in the past ten years, variational methods have achieved a great success on these two issues, in this thesis, we continue to work on proposing several new variational approaches for restoring and segmenting an image. This thesis contains two parts. The first part addresses recovering an image and the second part emphasizes on segmenting. Along with the wide utilization of magnetic resonance imaging (MRI) technique, we particularly deal with blurry images corrupted by Rician noise. In chapter 1, two new convex variational models for recovering an image corrupted by Rician noise with blur are presented. These two models are motivated by the non-convex maximum-a-posteriori (MAP) model proposed in the prior papers. In the first method, we use an approximation item to the zero order of the modified Bessel function in the MAP model and add an entropy-like item to obtain a convex model. Through studying on the statistical properties of Rician noise, we bring up a strictly convex model by adding an additional data-fidelity term in the MAP model in the second method. Primal-dual methods are applied to solve the models. The simulation outcomes show that our models outperform some existed effective models in both recovery image quality and computational time. Cone beam CT (CBCT) is routinely applied in image guided radiation therapy (IGRT) to help patient setup. Its imaging dose, however, is still a concern, limiting its wide applications. It has been an active research topic to develop novel technologies for radiation dose reduction. In chapter 2, we propose an improvement of practical CBCT dose control scheme - temporal non-local means (TNLM) scheme for IGRT. We denoise the scanned image with low dose by using the previous images as prior knowledge. We combine deformation image registration and TNLM. Different from the TNLM, in the new method, for each pixel, the search range is not fixed, but based on the motion vector between the prior image and the obtained image. By doing this, it is easy to find the similar pixels in the previous images, but also can reduce the computational time since it does not need large search windows. The phantom and patient studies illuminate that the new method outperforms the original one in both image quality and computational time. In the second part, we present a two-stage method for segmenting an image corrupted by blur and Rician noise. The method is motivated by the two-stage segmentation method developed by the authors in 2013 and restoration method for images with Rician noise. First, based on the statistical properties of Rician noise, we present a new convex variant of the modified Mumford-Shah model to get the smooth cartoon part {dollar}u{dollar} of the image. Then, we cluster the cartoon {dollar}u{dollar} into different parts to obtain the final contour of different phases of the image. Moreover, {dollar}u{dollar} from the first stage is unique because of the convexity of the new model, and it needs to be computed only once whenever the thresholds and the number of the phases {dollar}K{dollar} in the second stage change. We implement the simulation on the synthetic and real images to show that our model outperforms some existed segmentation models in both precision and computational time

In compressive imaging the measurement quantization and its impact on the overall system performance is an important problem. This work considers several challenges that derive from quantization of compressive measurements. We investigate the design of scalar quantizer (SQ), vector quantizer (VQ), and tree-structured vector quantizer (TSVQ) for information-optimal compressive imaging. The performance of these quantizer designs is quantified for a variety of compression rates and measurement signal-to-noise-ratio (SNR) using simulation studies. Our simulation results show that in the low SNR regime a low bit-depth (3 bit per measurement) SQ is sufficient to minimize the degradation due to measurement quantization. However, in mid-to-high SNR regime, quantizer design requires higher bit-depth to preserve the information in the measurements. Simulation results also confirm the superior performance of VQ over SQ. As expected, TSVQ provides a good tradeoff between complexity and performance, bounded by VQ and SQ designs on either side of performance/complexity limits. In compressive image the size of final measurement data (i.e. in bits) is also an important system design metric. In this work, we also optimize the compressive imaging system using this design metric, and investigate how to optimally allocate the number of measurement and bits per measurement, i.e. the rate allocation problem. This problem is solved using both an empirical data driven approach and a model-based approach. As a function of compression rate (bits per pixel), our simulation results show that compressive imaging can outperform traditional (non-compressive) imaging followed by image compression (JPEG 2000) in low-to-mid SNR regime. However, in high SNR regime traditional imaging (with image compression) offers a higher image fidelity compare to compressive imaging for a given data rate. Compressive imaging using blockwise measurements is partly limited due to its inability to perform global rate allocation. We also develop an optimal minimum mean-square error (MMSE) reconstruction algorithm for quantized compressed measurements. The algorithm employs Monte-Carlo Markov Chain (MCMC) sampling technique to estimate the posterior mean. Simulation results show significant improvement over approximate MMSE algorithms.

Les méthodes de microscopie de super-résolution (SRM) telles que la microscopie PALM (photoactivated localization microscopy), STORM (stochastic optical reconstruction microscopy), BALM (binding-activated localization microscopy) et le DNA-PAINT, représentent un nouvel ensemble de techniques de microscopie optique qui permettent de surpasser la limite de diffraction ( > 200 nm dans le spectre visible). Ces méthodes sont basées sur la localisation de la fluorescence de molécules uniques, et peuvent atteindre des résolutions de l'ordre du nanomètres (~20 nm latéralement et 50 nm axialement). Les techniques SRM ont un large spectre d'applications dans les domaines de la biologie et de la biophysique, rendant possible l'accès à l'information tant dynamique que structurale de structures connues ou non, in vivo et in vitro. Beaucoup d'efforts ont été fournis durant la dernière décennie afin d'élargir le potentiel de ces méthodes en développant des méthodes de localisation à la fois plus précise et plus rapide, d'améliorer la photophysique des fluorophores, de développer des algorithmes pour obtenir une information quantitative et augmenter la précision de localisation, etc. Cependant, très peu de méthodes ont été développées pour examiner l'hétérogénéité des images et extraire les informations statistiquement pertinent à partir de plusieurs milliers d'images individuelles super-résolues. Dans mon travail de thèse, je me suis spécifiquement attaquée à ces limitations en: (1) construisant des objets de dimensions nanométriques et de structures bien définies, avec la possibilité d'être adaptés aux besoins. Ces objets sont basés sur les origamis d'ADN. (2) développant des approches de marquage afin d'acquérir des images homogènes de ces objets. (3) implémentant des outils statistiques dans le but d'améliorer l'analyse et la validation d'images. Ces outils se basent sur des méthodes de reconstruction de molécules uniques communément appliquées aux reconstructions d'images de microscopie électronique. J'ai spécifiquement appliqué ces développements à la reconstruction de formes 3D de deux origamis d'ADN modèles (en une et trois dimensions). Je montre comment ces méthodes permettent la dissection de l'hétérogénéité de l'échantillon, et la combinaison d'images similaires afin d'améliorer le rapport signal sur bruit. La combinaison de différentes classes moyennes ont permis la reconstruction des formes tridimensionnelles des origamis d'ADN. Particulièrement, car cette méthode utilise la projection 2D de différentes vues d'une même structure, elle permet la récupération de résolutions isotropes en trois dimensions. Des fonctions spécifiques ont été adaptées à partir de méthodologies existantes afin de quantifier la fiabilité des reconstructions et de leur résolution. A l'avenir, ces développements seront utiles pour la reconstruction 3D de tous types d'objets biologiques pouvant être observés à haute résolution par des méthodologies dérivées de PALM, STORM ou PAINT. / Super resolution microscopy (SRM) methods such as photoactivated localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), binding-activated localization microscopy (BALM) and DNA-PAINT represent a new collection of light microscopy techniques that allow to overpass the diffraction limit barrier ( > 200 nm in the visible spectrum). These methods are based on the localization of bursts of fluorescence from single fluorophores, and can reach nanometer resolutions (~20 nm in lateral and 50 nm in axial direction, respectively). SRM techniques have a broad spectrum of applications in the field of biology and biophysics, allowing access to structural and dynamical information of known and unknown biological structures in vivo and in vitro. Many efforts have been made over the last decade to increase the potential of these methods by developing more precise and faster localization techniques, to improve fluorophore photophysics, to develop algorithms to obtain quantitative information and increase localization precision, etc. However, very few methods have been developed to dissect image heterogeneity and to extract statistically relevant information from thousands of individual super-resolved images. In my thesis, I specifically tackled these limitations by: (1) constructing objects with nanometer dimensions and well-defined structures with the possibility of be tailored to any need. These objects are based on DNA origami. (2) developing labeling approaches to homogeneously image these objects. These approaches are based on adaptations of BALM and DNA-PAINT microscopies. (3) implemented statistical tools to improve image analysis and validation. These tools are based on single-particle reconstruction methods commonly applied to image reconstruction in electron microscopy.I specifically applied these developments to reconstruct the 3D shape of two model DNA origami (in one and three dimensions). I show how this method permits the dissection of sample heterogeneity, and the combination of similar images in order to improve the signal-to-noise ratio. The combination of different average classes permitted the reconstruction of the three dimensional shape of DNA origami. Notably, because this method uses the 2D projections of different views of the same structure, it permits the recovery of isotropic resolutions in three dimensions. Specific functions were adapted from previous methodologies to quantify the reliability of the reconstructions and their resolution.In future, these developments will be helpful for the 3D reconstruction of any biological object that can be imaged at super resolution by PALM, STORM or PAINT-derived methodologies.

La tomographie consiste à reconstruire un objet nD à partir de projections (n-1)D. Cette discipline soulève plusieurs questions auxquelles la recherche essaie d’apporter des réponses. On s’intéresse dans cette thèse à trois aspects de cette problématique : 1) la reconstruction de l’image 2D à partir de projections dans un cadre rarement étudié qui est celui des sources ponctuelles ; 2) l’unicité de cette reconstruction ; 3) l'estimation d’informations concernant un objet sans passer par l'étape de reconstitution de son image. Afin d’aborder le problème de reconstruction pour la classe des ensembles convexes, nous définissons une nouvelle classe d’ensembles ayant des propriétés de convexité qu’on appelle convexité par quadrants pour des sources ponctuelles. Après une étude de cette nouvelle classe d’ensembles, nous montrons qu’elle présente des liens forts avec la classe des ensembles convexes. Nous proposons alors un algorithme de reconstruction d’ensemblesconvexes par quadrants qui, si l’unicité de la reconstruction est garantie, permet de reconstruire des ensembles convexes en un temps polynomial. Nous montrons que si une conjecture, que nous avons proposée, est vraie, les conditions de l’unicité pour les ensembles convexes par quadrants sont les mêmes que celles pour les ensembles convexes. Concernant le troisième aspect étudié dans cette thèse, nous proposons une méthode qui permet d’estimer, à partir d’une seule projection, la surface d’un ensemble 2D. Concernant l’estimation du périmètre d’un ensemble 2D, en considérant les projections par une deuxième source d’un ensemble convexe, nous obtenons deux bornes inférieures et une borne supérieure pour le périmètre de l’objet projeté. / Tomography is about reconstructing an nD object from its (n-1)D projections. This discipline addresses many questions to which research tries to provide answers. In this work, we are interested to three aspects: 1) the 2D image reconstruction from projections in a rarely studies framework that is the point sources; 2) the uniqueness of this reconstruction; 3) estimating information about an object without going through the step of reconstructing its image. To approach the problem of tomographic reconstruction for the class of convex sets, we define a new class of sets having properties of convexity called quadrant convexity for point sources. After a study of this new class of sets, we show that it presents strong links with the class of convex sets. Wepropose a reconstruction algorithm for quadrant-convex sets that, if the uniqueness of the reconstruction is guaranteed, allows the reconstruction of convex sets in polynomial time. We also show that if a conjecture we have proposed is true the conditions of uniqueness for quadrant-convex sets are the same as those for convex sets. Regarding the third aspect studied in this thesis, we focus on two quantitative properties that are the surface and the perimeter. We propose a method to estimate, from only one projection, the surface of a 2D set. We obtain two lower bounds and an upper bound for the perimeter of a projected convexobject by considering the projections from a second point source.

X-ray CT based baggage scanners are widely used in security applications. Recently, there has been increased interest in view-limited systems which can improve the scanning throughput while maintaining the threat detection performance. However as very few view angles are acquired in these systems, the image reconstruction problem is challenging. Standard reconstruction algorithms such as the filtered backprojection create strong artifacts when working with view-limited data. In this work, we study the performance of a variety of reconstruction algorithms for both single and multi-energy view-limited systems.