59 research outputs found

    Development and Implementation of Fully 3D Statistical Image Reconstruction Algorithms for Helical CT and Half-Ring PET Insert System

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    X-ray computed tomography: CT) and positron emission tomography: PET) have become widely used imaging modalities for screening, diagnosis, and image-guided treatment planning. Along with the increased clinical use are increased demands for high image quality with reduced ionizing radiation dose to the patient. Despite their significantly high computational cost, statistical iterative reconstruction algorithms are known to reconstruct high-quality images from noisy tomographic datasets. The overall goal of this work is to design statistical reconstruction software for clinical x-ray CT scanners, and for a novel PET system that utilizes high-resolution detectors within the field of view of a whole-body PET scanner. The complex choices involved in the development and implementation of image reconstruction algorithms are fundamentally linked to the ways in which the data is acquired, and they require detailed knowledge of the various sources of signal degradation. Both of the imaging modalities investigated in this work have their own set of challenges. However, by utilizing an underlying statistical model for the measured data, we are able to use a common framework for this class of tomographic problems. We first present the details of a new fully 3D regularized statistical reconstruction algorithm for multislice helical CT. To reduce the computation time, the algorithm was carefully parallelized by identifying and taking advantage of the specific symmetry found in helical CT. Some basic image quality measures were evaluated using measured phantom and clinical datasets, and they indicate that our algorithm achieves comparable or superior performance over the fast analytical methods considered in this work. Next, we present our fully 3D reconstruction efforts for a high-resolution half-ring PET insert. We found that this unusual geometry requires extensive redevelopment of existing reconstruction methods in PET. We redesigned the major components of the data modeling process and incorporated them into our reconstruction algorithms. The algorithms were tested using simulated Monte Carlo data and phantom data acquired by a PET insert prototype system. Overall, we have developed new, computationally efficient methods to perform fully 3D statistical reconstructions on clinically-sized datasets

    Effect of Biodiversity Changes in Disease Risk: Exploring Disease Emergence in a Plant-Virus System

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    The effect of biodiversity on the ability of parasites to infect their host and cause disease (i.e. disease risk) is a major question in pathology, which is central to understand the emergence of infectious diseases, and to develop strategies for their management. Two hypotheses, which can be considered as extremes of a continuum, relate biodiversity to disease risk: One states that biodiversity is positively correlated with disease risk (Amplification Effect), and the second predicts a negative correlation between biodiversity and disease risk (Dilution Effect). Which of them applies better to different host-parasite systems is still a source of debate, due to limited experimental or empirical data. This is especially the case for viral diseases of plants. To address this subject, we have monitored for three years the prevalence of several viruses, and virus-associated symptoms, in populations of wild pepper (chiltepin) under different levels of human management. For each population, we also measured the habitat species diversity, host plant genetic diversity and host plant density. Results indicate that disease and infection risk increased with the level of human management, which was associated with decreased species diversity and host genetic diversity, and with increased host plant density. Importantly, species diversity of the habitat was the primary predictor of disease risk for wild chiltepin populations. This changed in managed populations where host genetic diversity was the primary predictor. Host density was generally a poorer predictor of disease and infection risk. These results support the dilution effect hypothesis, and underline the relevance of different ecological factors in determining disease/infection risk in host plant populations under different levels of anthropic influence. These results are relevant for managing plant diseases and for establishing conservation policies for endangered plant species

    Reflecting on loss in Papua New Guinea

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    This article takes up the conundrum of conducting anthropological fieldwork with people who claim that they have 'lost their culture,' as is the case with Suau people in the Massim region of Papua New Guinea. But rather than claiming culture loss as a process of dispossession, Suau claim it as a consequence of their own attempts to engage with colonial interests. Suau appear to have responded to missionization and their close proximity to the colonial-era capital by jettisoning many of the practices characteristic of Massim societies, now identified as 'kastom.' The rejection of kastom in order to facilitate their relations with Europeans during colonialism, followed by the mourning for kastom after independence, both invite consideration of a kind of reflexivity that requires action based on the presumed perspective of another

    Effects of extreme natural events on the provision of ecosystem services in a mountain environment : The importance of trail design in delivering system resilience and ecosystem service co-benefits

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    A continued supply of ecosystem services (ES) from a system depends on the resilience of that system to withstand shocks and perturbations. In many parts of the world, climate change is leading to an increased frequency of extreme weather events, potentially influencing ES provision. Our study of the effects of an intense rainfall event in Gorce National Park, Poland, shows: (1) the intense rainfall event impacted heavily on the supply of ES by limiting potential recreation opportunities and reducing erosion prevention; (2) these negative impacts were not only restricted to the period of the extreme event but persisted for up to several years, depending on the pre-event trail conditions and post-event management activities; (3) to restore the pre-event supply of ES, economic investments were required in the form of active repairs to trails, which, in Gorce National Park, were an order of magnitude higher than the costs of normal trail maintenance; and (4) when recreational trails were left to natural restoration, loss of biodiversity was observed, and recovery rates of ES (recreation opportunities and soil erosion prevention) were reduced in comparison to their pre-event state. We conclude that proper trail design and construction provides a good solution to avoid some of the negative impacts of extreme events on recreation, as well as offering co-benefits in terms of protecting biodiversity and enhancing the supply of regulating services such as erosion prevention

    MISSING DATA ESTIMATION FOR FULLY 3D SPIRAL CT IMAGE RECONSTRUCTION

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    Reconstruction algorithms that are not set up to handle in-complete datasets can lead to artifacts in the reconstructed images because the assumptions regarding the size of the image space and/or data space are violated. In this study, two recently developed geometry-independent methods 1 are applied to fully 3D multi-slice spiral CT image recon-struction. Using simulated and clinical datasets, we dem-onstrate the effectiveness of the missing data approaches in improving the quality of slices that have experienced truncation in either the transverse or longitudinal direction. • When the support of an object lies partially outside the field of view (FOV) of a CT scanner, artifacts may arise in the reconstructed image due to undersampling. • Most reconstruction algorithms implicitly assume the entire object is confined to the FOV, but if this is not the case, excessively large attenuation values may be recon-structed inside the boundary of the FOV. • The reconstruction algorithm is unaware that the mea-sured data has been affected by the object's attenuation outside the FOV, so the image in the FOV is recon-structed such that the projections through it match the measured data
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