148 resultados para Camera Network, Image Processing, Compression
Resumo:
Detailed knowledge of the anatomy and connectivity pattern of cortico-basal ganglia circuits is essential to an understanding of abnormal cortical function and pathophysiology associated with a wide range of neurological and neuropsychiatric diseases. We aim to study the spatial extent and topography of human basal ganglia connectivity in vivo. Additionally, we explore at an anatomical level the hypothesis of coexistent segregated and integrative cortico-basal ganglia loops. We use probabilistic tractography on magnetic resonance diffusion weighted imaging data to segment basal ganglia and thalamus in 30 healthy subjects based on their cortical and subcortical projections. We introduce a novel method to define voxel-based connectivity profiles that allow representation of projections from a source to more than one target region. Using this method, we localize specific relay nuclei within predefined functional circuits. We find strong correlation between tractography-based basal ganglia parcellation and anatomical data from previously reported invasive tracing studies in nonhuman primates. Additionally, we show in vivo the anatomical basis of segregated loops and the extent of their overlap in prefrontal, premotor, and motor networks. Our findings in healthy humans support the notion that probabilistic diffusion tractography can be used to parcellate subcortical gray matter structures on the basis of their connectivity patterns. The coexistence of clearly segregated and also overlapping connections from cortical sites to basal ganglia subregions is a neuroanatomical correlate of both parallel and integrative networks within them. We believe that this method can be used to examine pathophysiological concepts in a number of basal ganglia-related disorders.
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A magnetic resonance imaging (MRI) pulse sequence and a corresponding image processing algorithm to localize prostate brachytherapy seeds during or after therapy are presented. Inversion-Recovery with ON-resonant water suppression (IRON) is an MRI methodology that generates positive contrast in regions of magnetic field susceptibility, as created by prostate brachytherapy seeds. Phantoms comprising of several materials found in brachytherapy seeds were created to assess the usability of the IRON pulse sequence for imaging seeds. Resulting images show that seed materials are clearly visible with high contrast using IRON, agreeing with theoretical predictions. A seed localization algorithm to process IRON images demonstrates the potential of this imaging technique for seed localization and dosimetry.
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Protein oxidation and ubiquitination of brain proteins are part of mechanisms that modulate protein function or that inactivate proteins and target misfolded proteins to degradation. In this study, we focused on brain aging and on mechanism involved in neurodegeneration such as events occurring in Alzheimer's disease (AD). The goal was to identify differences in nitrosylated proteins - at cysteine residues, and in the composition of ubiquinated proteins between aging and Alzheimer's samples by using a proteomic approach. A polyclonal anti-S-nitrosyl-cysteine, a mono- and a polyclonal anti-ubiquitin antibody were used for the detection of modified or ubiquitinated proteins in middle-aged and aged human entorhinal autopsy brains tissues of 14 subjects without neurological signs and 8 Alzheimer's patients. Proteins were separated by one- and two-dimensional gel electrophoresis and analyzed by Coomassie blue and immuno-blot staining. We identified that the glial fibrillary acidic and tau proteins are more ubiquitinated in brain tissues of Alzheimer's patients. Furthermore, glial fibrillary proteins were also found in nitrosylated state and further characterized by 2D Western blots and identified. Since reactive astrocytes localized prominently around senile plaques one can speculate that elements of plaques such as beta-amyloid proteins may activate surrounding glial elements and proteins.
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This work compares the detector performance and image quality of the new Kodak Min-R EV mammography screen-film system with the Fuji CR Profect detector and with other current mammography screen-film systems from Agfa, Fuji and Kodak. Basic image quality parameters (MTF, NPS, NEQ and DQE) were evaluated for a 28 kV Mo/Mo (HVL = 0.646 mm Al) beam using different mAs exposure settings. Compared with other screen-film systems, the new Kodak Min-R EV detector has the highest contrast and a low intrinsic noise level, giving better NEQ and DQE results, especially at high optical density. Thus, the properties of the new mammography film approach those of a fine mammography detector, especially at low frequency range. Screen-film systems provide the best resolution. The presampling MTF of the digital detector has a value of 15% at the Nyquist frequency and, due to the spread size of the laser beam, the use of a smaller pixel size would not permit a significant improvement of the detector resolution. The dual collection reading technology increases significantly the low frequency DQE of the Fuji CR system that can at present compete with the most efficient mammography screen-film systems.
Resumo:
BACKGROUND: Since the emergence of diffusion tensor imaging, a lot of work has been done to better understand the properties of diffusion MRI tractography. However, the validation of the reconstructed fiber connections remains problematic in many respects. For example, it is difficult to assess whether a connection is the result of the diffusion coherence contrast itself or the simple result of other uncontrolled parameters like for example: noise, brain geometry and algorithmic characteristics. METHODOLOGY/PRINCIPAL FINDINGS: In this work, we propose a method to estimate the respective contributions of diffusion coherence versus other effects to a tractography result by comparing data sets with and without diffusion coherence contrast. We use this methodology to assign a confidence level to every gray matter to gray matter connection and add this new information directly in the connectivity matrix. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that whereas we can have a strong confidence in mid- and long-range connections obtained by a tractography experiment, it is difficult to distinguish between short connections traced due to diffusion coherence contrast from those produced by chance due to the other uncontrolled factors of the tractography methodology.
Resumo:
The RuvB protein is induced in Escherichia coli as part of the SOS response to DNA damage. It is required for genetic recombination and the postreplication repair of DNA. In vitro, the RuvB protein promotes the branch migration of Holliday junctions and has a DNA helicase activity in reactions that require ATP hydrolysis. We have used electron microscopy, image analysis, and three-dimensional reconstruction to show that the RuvB protein, in the presence of ATP, forms a dodecamer on double-stranded DNA in which two stacked hexameric rings encircle the DNA and are oriented in opposite directions with D6 symmetry. Although helicases are ubiquitous and essential for many aspects of DNA repair, replication, and transcription, three-dimensional reconstruction of a helicase has not yet been reported, to our knowledge. The structural arrangement that is seen may be common to other helicases, such as the simian virus 40 large tumor antigen.
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A precise classification and an optimal understanding of tibial plateau fractures are the basis of a conservative treatment or adequate surgery. The aim of this prospective study is to determine the contribution of 3D CT to the classification of fractures (comparison with standard X-rays) and as an aid to the surgeon in preoperative planning and surgical reconstruction. Between November 1994 and July 1996, 20 patients presenting 22 tibial plateau fractures were considered in this study. They all underwent surgical treatment. The fractures were classified according to the Müller AO classification. They were all investigated by means of standard X-rays (AP, profile, oblique) and the 3D CT. Analysis of the results has shown the superiority of 3D CT in the planning (easier and more acute), in the classification (more precise), and in the exact assessment of the lesions (quantity of fragments); thereby proving to be of undeniable value of the surgeon.
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This paper presents a method to reconstruct 3D surfaces of silicon wafers from 2D images of printed circuits taken with a scanning electron microscope. Our reconstruction method combines the physical model of the optical acquisition system with prior knowledge about the shapes of the patterns in the circuit; the result is a shape-from-shading technique with a shape prior. The reconstruction of the surface is formulated as an optimization problem with an objective functional that combines a data-fidelity term on the microscopic image with two prior terms on the surface. The data term models the acquisition system through the irradiance equation characteristic of the microscope; the first prior is a smoothness penalty on the reconstructed surface, and the second prior constrains the shape of the surface to agree with the expected shape of the pattern in the circuit. In order to account for the variability of the manufacturing process, this second prior includes a deformation field that allows a nonlinear elastic deformation between the expected pattern and the reconstructed surface. As a result, the minimization problem has two unknowns, and the reconstruction method provides two outputs: 1) a reconstructed surface and 2) a deformation field. The reconstructed surface is derived from the shading observed in the image and the prior knowledge about the pattern in the circuit, while the deformation field produces a mapping between the expected shape and the reconstructed surface that provides a measure of deviation between the circuit design models and the real manufacturing process.
Resumo:
BACKGROUND AND PURPOSE: Patients with symptoms of semicircular canal dehiscence often undergo both CT and MR imaging. We assessed whether FIESTA can replace temporal bone CT in evaluating patients for SC dehiscence. MATERIALS AND METHODS: We retrospectively reviewed 112 consecutive patients (224 ears) with vestibulocochlear symptoms who underwent concurrent MR imaging and CT of the temporal bones between 2007 and 2009. MR imaging protocol included a FIESTA sequence covering the temporal bone (axial 0.8-mm section thickness, 0.4-mm spacing, coronal/oblique reformations; 41 patients at 1.5T, 71 patients at 3T). CT was performed on a 64-row multidetector row scanner (0.625-mm axial acquisition, with coronal/oblique reformations). Both ears of each patient were evaluated for dehiscence of the superior and posterior semicircular canals in consensual fashion by 2 neuroradiologists. Analysis of the FIESTA sequence and reformations was performed first for the MR imaging evaluation. CT evaluation was performed at least 2 weeks after the MR imaging review, resulting in a blinded comparison of CT with MR imaging. CT was used as the reference standard to evaluate the MR imaging results. RESULTS: For SSC dehiscence, MR imaging sensitivity was 100%, specificity was 96.5%, positive predictive value was 61.1%, and negative predictive value was 100% in comparison with CT. For PSC dehiscence, MR imaging sensitivity was 100%, specificity was 99.1%, positive predictive value was 33.3%, and negative predictive value was 100% in comparison with CT. CONCLUSIONS: MR imaging, with a sensitivity and negative predictive value of 100%, conclusively excludes SSC or PSC dehiscence. Negative findings on MR imaging preclude the need for CT to detect SC dehiscence. Only patients with positive findings on MR imaging should undergo CT evaluation.
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Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.
Resumo:
PURPOSE: To examine the reproducibility of carotid artery dimension measurements using 3T MRI. MATERIALS AND METHODS: Ten healthy volunteers underwent three scans on two occasions for assessment of total vessel wall area (TVWA), total luminal area (TLA), and minimum (MinT) and maximum (MaxT) vessel wall thickness. A double inversion-recovery (IR) fast gradient-echo (FGRE) sequence was used on a commercial 3T system. During the first visit the subjects were scanned twice. The third scan was performed at least four days later. One observer traced all scans, and a second observer retraced the first scan series. RESULTS: For TVWA an interclass correlation (ICC) of 0.994 was calculated with all three scans taken into account. The interobserver ICC was 0.984. The agreement between the scans for TLA showed an ICC of 0.982 with an interobserver ICC of 0.998. For MinT and MaxT an ICC of 0.843 and 0.935 were calculated, with interobserver ICCs of 0.860 and 0.726, respectively. CONCLUSION: With the use of a commercial 3T MR system, TVWA, TLA, and wall thickness measurements of the carotid artery can be assessed with good reproducibility.
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We propose a compressive sensing algorithm that exploits geometric properties of images to recover images of high quality from few measurements. The image reconstruction is done by iterating the two following steps: 1) estimation of normal vectors of the image level curves, and 2) reconstruction of an image fitting the normal vectors, the compressed sensing measurements, and the sparsity constraint. The proposed technique can naturally extend to nonlocal operators and graphs to exploit the repetitive nature of textured images to recover fine detail structures. In both cases, the problem is reduced to a series of convex minimization problems that can be efficiently solved with a combination of variable splitting and augmented Lagrangian methods, leading to fast and easy-to-code algorithms. Extended experiments show a clear improvement over related state-of-the-art algorithms in the quality of the reconstructed images and the robustness of the proposed method to noise, different kind of images, and reduced measurements.