58 resultados para 3D scalar data
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A search for pair-produced third generation scalar leptoquarks is presented, using proton-proton collisions at root s = 7 TeV at the LHC. The data were recorded with the ATLAS detector and correspond to an integrated luminosity of 4.7 fb(-1). Each leptoquark is assumed to decay to a tau lepton and a b-quark with a branching fraction equal to 100%. No statistically significant excess above the Standard Model expectation is observed. Third generation leptoquarks are therefore excluded at 95% confidence level for masses less than 534 GeV.
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We propose a method to acquire 3D light fields using a hand-held camera, and describe several computational photography applications facilitated by our approach. As our input we take an image sequence from a camera translating along an approximately linear path with limited camera rotations. Users can acquire such data easily in a few seconds by moving a hand-held camera. We include a novel approach to resample the input into regularly sampled 3D light fields by aligning them in the spatio-temporal domain, and a technique for high-quality disparity estimation from light fields. We show applications including digital refocusing and synthetic aperture blur, foreground removal, selective colorization, and others.
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Accurate three-dimensional (3D) models of lumbar vertebrae are required for image-based 3D kinematics analysis. MRI or CT datasets are frequently used to derive 3D models but have the disadvantages that they are expensive, time-consuming or involving ionizing radiation (e.g., CT acquisition). In this chapter, we present an alternative technique that can reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image and a statistical shape model. Cadaveric studies are conducted to verify the reconstruction accuracy by comparing the surface models reconstructed from a single lateral fluoroscopic image to the ground truth data from 3D CT segmentation. A mean reconstruction error between 0.7 and 1.4 mm was found.
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In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively.
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In this paper, we propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. To detect landmarks, we estimate the displacements from some randomly sampled image patches to the (unknown) landmark positions, and then we integrate these predictions via a voting scheme. Our key contribution is a new algorithm for estimating these displacements. Different from other methods where each image patch independently predicts its displacement, we jointly estimate the displacements from all patches together in a data driven way, by considering not only the training data but also geometric constraints on the test image. The displacements estimation is formulated as a convex optimization problem that can be solved efficiently. Finally, we use the sparse shape composition model as the a priori information to regularize the landmark positions and thus generate the segmented shape contour. We validate our method on X-ray image datasets of three different anatomical structures: complete femur, proximal femur and pelvis. Experiments show that our method is accurate and robust in landmark detection, and, combined with the shape model, gives a better or comparable performance in shape segmentation compared to state-of-the art methods. Finally, a preliminary study using CT data shows the extensibility of our method to 3D data.
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Purpose Ophthalmologists are confronted with a set of different image modalities to diagnose eye tumors e.g., fundus photography, CT and MRI. However, these images are often complementary and represent pathologies differently. Some aspects of tumors can only be seen in a particular modality. A fusion of modalities would improve the contextual information for diagnosis. The presented work attempts to register color fundus photography with MRI volumes. This would complement the low resolution 3D information in the MRI with high resolution 2D fundus images. Methods MRI volumes were acquired from 12 infants under the age of 5 with unilateral retinoblastoma. The contrast-enhanced T1-FLAIR sequence was performed with an isotropic resolution of less than 0.5mm. Fundus images were acquired with a RetCam camera. For healthy eyes, two landmarks were used: the optic disk and the fovea. The eyes were detected and extracted from the MRI volume using a 3D adaption of the Fast Radial Symmetry Transform (FRST). The cropped volume was automatically segmented using the Split Bregman algorithm. The optic nerve was enhanced by a Frangi vessel filter. By intersection the nerve with the retina the optic disk was found. The fovea position was estimated by constraining the position with the angle between the optic and the visual axis as well as the distance from the optic disk. The optical axis was detected automatically by fitting a parable on to the lens surface. On the fundus, the optic disk and the fovea were detected by using the method of Budai et al. Finally, the image was projected on to the segmented surface using the lens position as the camera center. In tumor affected eyes, the manually segmented tumors were used instead of the optic disk and macula for the registration. Results In all of the 12 MRI volumes that were tested the 24 eyes were found correctly, including healthy and pathological cases. In healthy eyes the optic nerve head was found in all of the tested eyes with an error of 1.08 +/- 0.37mm. A successful registration can be seen in figure 1. Conclusions The presented method is a step toward automatic fusion of modalities in ophthalmology. The combination enhances the MRI volume with higher resolution from the color fundus on the retina. Tumor treatment planning is improved by avoiding critical structures and disease progression monitoring is made easier.
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Venous air embolism (VAE) is an often occurring forensic finding in cases of injury to the head and neck. Whenever found, it has to be appraised in its relation to the cause of death. While visualization and quantification is difficult at traditional autopsy, Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) offer a new potential in the diagnosis of VAE. This paper reports the findings of VAE in four cases of massive head injury examined postmortem by Multislice Computed Tomography (MSCT) prior to autopsy. MSCT data of the thorax were processed using 3D air structure reconstruction software to visualize air embolism within the vascular system. Quantification of VAE was done by multiplying air containing areas on axial 2D images by their reconstruction intervals and then by summarizing the air volumes. Excellent 3D visualization of the air within the vascular system was obtained in all cases, and the intravascular gas volume was quantified.
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67P/Churyumov-Gerasimenko (67P) is a Jupiter-family comet and the object of investigation of the European Space Agency mission Rosetta. This report presents the first full 3D simulation results of 67P’s neutral gas coma. In this study we include results from a direct simulation Monte Carlo method, a hydrodynamic code, and a purely geometric calculation which computes the total illuminated surface area on the nucleus. All models include the triangulated 3D shape model of 67P as well as realistic illumination and shadowing conditions. The basic concept is the assumption that these illumination conditions on the nucleus are the main driver for the gas activity of the comet. As a consequence, the total production rate of 67P varies as a function of solar insolation. The best agreement between the model and the data is achieved when gas fluxes on the night side are in the range of 7% to 10% of the maximum flux, accounting for contributions from the most volatile components. To validate the output of our numerical simulations we compare the results of all three models to in situ gas number density measurements from the ROSINA COPS instrument. We are able to reproduce the overall features of these local neutral number density measurements of ROSINA COPS for the time period between early August 2014 and January 1 2015 with all three models. Some details in the measurements are not reproduced and warrant further investigation and refinement of the models. However, the overall assumption that illumination conditions on the nucleus are at least an important driver of the gas activity is validated by the models. According to our simulation results we find the total production rate of 67P to be constant between August and November 2014 with a value of about 1 × 10²⁶ molecules s⁻¹.
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Background The RCSB Protein Data Bank (PDB) provides public access to experimentally determined 3D-structures of biological macromolecules (proteins, peptides and nucleic acids). While various tools are available to explore the PDB, options to access the global structural diversity of the entire PDB and to perceive relationships between PDB structures remain very limited. Methods A 136-dimensional atom pair 3D-fingerprint for proteins (3DP) counting categorized atom pairs at increasing through-space distances was designed to represent the molecular shape of PDB-entries. Nearest neighbor searches examples were reported exemplifying the ability of 3DP-similarity to identify closely related biomolecules from small peptides to enzyme and large multiprotein complexes such as virus particles. The principle component analysis was used to obtain the visualization of PDB in 3DP-space. Results The 3DP property space groups proteins and protein assemblies according to their 3D-shape similarity, yet shows exquisite ability to distinguish between closely related structures. An interactive website called PDB-Explorer is presented featuring a color-coded interactive map of PDB in 3DP-space. Each pixel of the map contains one or more PDB-entries which are directly visualized as ribbon diagrams when the pixel is selected. The PDB-Explorer website allows performing 3DP-nearest neighbor searches of any PDB-entry or of any structure uploaded as protein-type PDB file. All functionalities on the website are implemented in JavaScript in a platform-independent manner and draw data from a server that is updated daily with the latest PDB additions, ensuring complete and up-to-date coverage. The essentially instantaneous 3DP-similarity search with the PDB-Explorer provides results comparable to those of much slower 3D-alignment algorithms, and automatically clusters proteins from the same superfamilies in tight groups. Conclusion A chemical space classification of PDB based on molecular shape was obtained using a new atom-pair 3D-fingerprint for proteins and implemented in a web-based database exploration tool comprising an interactive color-coded map of the PDB chemical space and a nearest neighbor search tool. The PDB-Explorer website is freely available at www.cheminfo.org/pdbexplorer and represents an unprecedented opportunity to interactively visualize and explore the structural diversity of the PDB.
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The bacterial phosphoenolpyruvate: sugar phosphotransferase system serves the combined uptake and phosphorylation of carbohydrates. This structurally and functionally complex system is composed of several conserved functional units that, through a cascade of phosphorylated intermediates, catalyze the transfer of the phosphate moiety from phosphoenolpyruvate to the substrate, which is bound to the integral membrane domain IIC. The wild-type glucose-specific IIC domain (wt-IIC(glc)) of Escherichia coli was cloned, overexpressed and purified for biochemical and functional characterization. Size-exclusion chromatography and scintillation-proximity binding assays showed that purified wt-IIC(glc) was homogenous and able to bind glucose. Crystallization was pursued following two different approaches: (i) reconstitution of wt-IIC(glc) into a lipid bilayer by detergent removal through dialysis, which yielded tubular 2D crystals, and (ii) vapor-diffusion crystallization of detergent-solubilized wt-IIC(glc), which yielded rhombohedral 3D crystals. Analysis of the 2D crystals by cryo-electron microscopy and the 3D crystals by X-ray diffraction indicated resolutions of better than 6Å and 4Å, respectively. Furthermore, a complete X-ray diffraction data set could be collected and processed to 3.93Å resolution. These 2D and 3D crystals of wt-IIC(glc) lay the foundation for the determination of the first structure of a bacterial glucose-specific IIC domain.
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OBJECTIVES To determine the relationship between nasolabial symmetry and esthetics in subjects with orofacial clefts. MATERIAL AND METHODS Eighty-four subjects (mean age 10 years, standard deviation 1.5) with various types of nonsyndromic clefts were included: 11 had unilateral cleft lip (UCL); 30 had unilateral cleft lip and alveolus (UCLA); and 43 had unilateral cleft lip, alveolus, and palate (UCLAP). A 3D stereophotogrammetric image of the face was taken for each subject. Symmetry and esthetics were evaluated on cropped 3D facial images. The degree of asymmetry of the nasolabial area was calculated based on all 3D data points using a surface registration algorithm. Esthetic ratings of various elements of nasal morphology were performed by eight lay raters on a 100 mm visual analog scale. Statistical analysis included ANOVA tests and regression models. RESULTS Nasolabial asymmetry increased with growing severity of the cleft (p = 0.029). Overall, nasolabial appearance was affected by nasolabial asymmetry; subjects with more nasolabial asymmetry were judged as having a less esthetically pleasing nasolabial area (p < 0.001). However, the relationship between nasolabial symmetry and esthetics was relatively weak in subjects with UCLAP, in whom only vermilion border esthetics was associated with asymmetry. CONCLUSIONS Nasolabial symmetry assessed with 3D facial imaging can be used as an objective measure of treatment outcome in subjects with less severe cleft deformity. In subjects with more severe cleft types, other factors may play a decisive role. CLINICAL SIGNIFICANCE Assessment of nasolabial symmetry is a useful measure of treatment success in less severe cleft types.
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This paper presents a non-rigid free-from 2D-3D registration approach using statistical deformation model (SDM). In our approach the SDM is first constructed from a set of training data using a non-rigid registration algorithm based on b-spline free-form deformation to encode a priori information about the underlying anatomy. A novel intensity-based non-rigid 2D-3D registration algorithm is then presented to iteratively fit the 3D b-spline-based SDM to the 2D X-ray images of an unseen subject, which requires a computationally expensive inversion of the instantiated deformation in each iteration. In this paper, we propose to solve this challenge with a fast B-spline pseudo-inversion algorithm that is implemented on graphics processing unit (GPU). Experiments conducted on C-arm and X-ray images of cadaveric femurs demonstrate the efficacy of the present approach.
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PURPOSE The purpose of this study was to identify morphologic factors affecting type I endoleak formation and bird-beak configuration after thoracic endovascular aortic repair (TEVAR). METHODS Computed tomography (CT) data of 57 patients (40 males; median age, 66 years) undergoing TEVAR for thoracic aortic aneurysm (34 TAA, 19 TAAA) or penetrating aortic ulcer (n = 4) between 2001 and 2010 were retrospectively reviewed. In 28 patients, the Gore TAG® stent-graft was used, followed by the Medtronic Valiant® in 16 cases, the Medtronic Talent® in 8, and the Cook Zenith® in 5 cases. Proximal landing zone (PLZ) was in zone 1 in 13, zone 2 in 13, zone 3 in 23, and zone 4 in 8 patients. In 14 patients (25%), the procedure was urgent or emergent. In each case, pre- and postoperative CT angiography was analyzed using a dedicated image processing workstation and complimentary in-house developed software based on a 3D cylindrical intensity model to calculate aortic arch angulation and conicity of the landing zones (LZ). RESULTS Primary type Ia endoleak rate was 12% (7/57) and subsequent re-intervention rate was 86% (6/7). Left subclavian artery (LSA) coverage (p = 0.036) and conicity of the PLZ (5.9 vs. 2.6 mm; p = 0.016) were significantly associated with an increased type Ia endoleak rate. Bird-beak configuration was observed in 16 patients (28%) and was associated with a smaller radius of the aortic arch curvature (42 vs. 65 mm; p = 0.049). Type Ia endoleak was not associated with a bird-beak configuration (p = 0.388). Primary type Ib endoleak rate was 7% (4/57) and subsequent re-intervention rate was 100%. Conicity of the distal LZ was associated with an increased type Ib endoleak rate (8.3 vs. 2.6 mm; p = 0.038). CONCLUSIONS CT-based 3D aortic morphometry helps to identify risk factors of type I endoleak formation and bird-beak configuration during TEVAR. These factors were LSA coverage and conicity within the landing zones for type I endoleak formation and steep aortic angulation for bird-beak configuration.