Super Resolution of HARDI images Using Compressed Sensing Techniques

Effective techniques of inferring the condition of neural tracts in the brain is invaluable for clinicians and researchers towards investigation of neurological disorders in patients. It was not until the advent of diffusion Magnetic Resonance Imaging (dMRI), a noninvasive imaging method used to detect the diffusion of water molecules, that scientists have been able to assess the characteristics of cerebral diffusion in vivo. Among different dMRI methods, High Angular Resolution Diffusion Imaging (HARDI) is well known for striking a balance between ability to distinguish crossing neural fibre tracts while requiring a modest number of diffusion measurements (which is directly related to acquisition time). HARDI data provides insight into the directional properties of water diffusion in cerebral matter as a function of spatial coordinates. Ideally, one would be interested in having this information available at fine spatial resolution while minimizing the probing along different spatial orientations (so as to minimize the acquisition time). Unfortunately, availability of such datasets in reasonable acquisition times are hindered by limitations in current hardware and scanner protocols. On the other hand, post processing techniques prove promising in increasing the effective spatial resolution, allowing more detailed depictions of cerebral matter, while keeping the number of diffusion measurements within a feasible range. In light of the preceding developments, the main purpose of this research is to look into super resolution of HARDI data, using the modern theory of compressed sensing. The method proposed in this thesis allows an accurate approximation of HARDI signals at a higher spatial resolution compared to data obtained with a typical scanner. At the same time, ideas for reducing the number of diffusion measurements in the angular domain to improve the acquisition time are explored. Accordingly, the novel method of applying two distinct compressed sensing approaches in both spatial and angular domain, and combining them into a single framework for performing super resolution forms the main contribution provided by this thesis

Interactive Multi-volume Visualization

Abstract. This paper is concerned with simultaneous visualization of two or more volumes, which may be from different imaging modalities or numerical simulations for the same subject of study. The main visualization challenge is to establish visual correspondences while maintaining distinctions among multiple volumes. One solution is to use different rendering styles for different volumes. Interactive rendering is required so the user can choose with ease an appropriate rendering style and its associated parameters for each volume. Rendering effi-ciency is maximized by utilizing commodity graphics cards. We demonstrate our preliminary results with two case studies.

Architecture as artform : drawing, painting, collage, and architecture, 1945-1965

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Architecture, 1999.Includes bibliographical references (p. 319-329).The development of an American architectural avant-garde after the Second World War is examined in relation to the formal properties and institutionalized cultural authority of modern art. Rather than looking to the artwork of their American artistic contemporaries, architects and critics appropriated the early European avant-garde as typological precedents, guided by a pedagogical approach steeped in Bauhaus teaching methods. Drawing became the common conduit between the abstract work of art and its transformation into modern architecture. Architecture was seen as a problem that could be studied diagrammatically, and consequently also thought of as a fundamentally conceptual, immaterial artifact. At the same time that architecture was moving towards a flattened artistic condition, however, abstract expressionist painting began to take on the material and dimensional properties of the architectural object, demarcating volume and structure. Modernist collage techniques were also introduced into postwar architectural design, but again the material aspects of the medium were suppressed in favor of its purely visual qualities.by Eric K. Lum.Ph.D

Identification of Human Sperm Antigens to Antisperm Antibodies *

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98396/1/j.1600-0897.1983.tb00243.x.pd

Increasing the Power to Detect Causal Associations by Combining Genotypic and Expression Data in Segregating Populations

To dissect common human diseases such as obesity and diabetes, a systematic approach is needed to study how genes interact with one another, and with genetic and environmental factors, to determine clinical end points or disease phenotypes. Bayesian networks provide a convenient framework for extracting relationships from noisy data and are frequently applied to large-scale data to derive causal relationships among variables of interest. Given the complexity of molecular networks underlying common human disease traits, and the fact that biological networks can change depending on environmental conditions and genetic factors, large datasets, generally involving multiple perturbations (experiments), are required to reconstruct and reliably extract information from these networks. With limited resources, the balance of coverage of multiple perturbations and multiple subjects in a single perturbation needs to be considered in the experimental design. Increasing the number of experiments, or the number of subjects in an experiment, is an expensive and time-consuming way to improve network reconstruction. Integrating multiple types of data from existing subjects might be more efficient. For example, it has recently been demonstrated that combining genotypic and gene expression data in a segregating population leads to improved network reconstruction, which in turn may lead to better predictions of the effects of experimental perturbations on any given gene. Here we simulate data based on networks reconstructed from biological data collected in a segregating mouse population and quantify the improvement in network reconstruction achieved using genotypic and gene expression data, compared with reconstruction using gene expression data alone. We demonstrate that networks reconstructed using the combined genotypic and gene expression data achieve a level of reconstruction accuracy that exceeds networks reconstructed from expression data alone, and that fewer subjects may be required to achieve this superior reconstruction accuracy. We conclude that this integrative genomics approach to reconstructing networks not only leads to more predictive network models, but also may save time and money by decreasing the amount of data that must be generated under any given condition of interest to construct predictive network models

Severe dengue categories as research endpoints-Results from a prospective observational study in hospitalised dengue patients.

Severe dengue was perceived as one clinical disease entity until the WHO 2009 classification stratified it into severe vascular leakage, severe bleeding, and severe organ dysfunction. The objectives of this study were to investigate the potential use of severe dengue categories as endpoints for intervention research. 271 patients with severe dengue among 1734 confirmed dengue patients were followed prospectively in this hospital-based observational study in Latin America and Asia. We compared the distribution of severe dengue categories according to gender and age (below/above 15y), and determined the relative frequency and the overlap of severe dengue categories in the same patients. In a next step, we extended the analysis to candidate moderate severity categories, based on recently suggested definitions which were adapted for our purposes. Severe vascular leakage occurred in 244 (90%), severe bleeding in 39 (14%), and severe organ dysfunction in 28 (10%) of 271 severe dengue patients. A higher frequency of severe leakage was seen in children or adolescents (<15y) compared to adults. More than 80% of the severe leakage cases, and 30-50% of the cases with severe bleeding or severe organ dysfunction, were defined as severe on the basis of that feature alone. In 136 out of 213 patients with severe leakage alone, neither moderate bleeding manifestation nor hepatic involvement was recorded. On the other hand, moderate leakage manifestations were detected in 4 out of 12 cases that were classified as severe based on bleeding alone. A major proportion of severe dengue patients exhibited clinical manifestations of severe vascular leakage only, which may constitute a useful endpoint for intervention research or pathophysiology studies. Severe bleeding and severe organ manifestation were recorded less frequently and exhibited a higher degree of overlap with severe leakage. Severe bleeding without leakage may be associated with individual predisposition or the presence of comorbidities. More detailed assessments are needed to explore this hypothesis. Candidate moderate disease endpoints were investigated and need to be further validated