987 resultados para Imaging, Three-Dimensional


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BACKGROUND Current guidelines for evaluating cleft palate treatments are mostly based on two-dimensional (2D) evaluation, but three-dimensional (3D) imaging methods to assess treatment outcome are steadily rising. OBJECTIVE To identify 3D imaging methods for quantitative assessment of soft tissue and skeletal morphology in patients with cleft lip and palate. DATA SOURCES Literature was searched using PubMed (1948-2012), EMBASE (1980-2012), Scopus (2004-2012), Web of Science (1945-2012), and the Cochrane Library. The last search was performed September 30, 2012. Reference lists were hand searched for potentially eligible studies. There was no language restriction. STUDY SELECTION We included publications using 3D imaging techniques to assess facial soft tissue or skeletal morphology in patients older than 5 years with a cleft lip with/or without cleft palate. We reviewed studies involving the facial region when at least 10 subjects in the sample size had at least one cleft type. Only primary publications were included. DATA EXTRACTION Independent extraction of data and quality assessments were performed by two observers. RESULTS Five hundred full text publications were retrieved, 144 met the inclusion criteria, with 63 high quality studies. There were differences in study designs, topics studied, patient characteristics, and success measurements; therefore, only a systematic review could be conducted. Main 3D-techniques that are used in cleft lip and palate patients are CT, CBCT, MRI, stereophotogrammetry, and laser surface scanning. These techniques are mainly used for soft tissue analysis, evaluation of bone grafting, and changes in the craniofacial skeleton. Digital dental casts are used to evaluate treatment and changes over time. CONCLUSION Available evidence implies that 3D imaging methods can be used for documentation of CLP patients. No data are available yet showing that 3D methods are more informative than conventional 2D methods. Further research is warranted to elucidate it.

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OBJECTIVE The objective of the study is to investigate the electrocortical and the global cognitive effects of 3 months rivastigmine medication in a group of mild to moderate Alzheimer's disease patients. MATERIALS AND METHODS Multichannel EEG and cognitive performances measured with the Mini Mental State Examination in a group of 16 patients with mild to moderate Alzheimer's Disease were collected before and 3 months after the onset of rivastigmine medication. RESULTS Spectral analysis of the EEG data showed a significant power decrease in the delta and theta frequency bands during rivastigmine medication, i.e., a shift of the power spectrum towards 'normalization'. Three-dimensional low resolution electromagnetic tomography (LORETA) functional imaging localized rivastigmine effects in a network that includes left fronto-parietal regions, posterior cingulate cortex, bilateral parahippocampal regions, and the hippocampus. Moreover, a correlation analysis between differences in the cognitive performances during the two recordings and LORETA-computed intracortical activity showed, in the alpha1 frequency band, better cognitive performance with increased cortical activity in the left insula. CONCLUSION The results point to a 'normalization' of the EEG power spectrum due to medication, and the intracortical localization of these effects showed an increase of cortical activity in frontal, parietal, and temporal regions that are well-known to be affected in Alzheimer's disease. The topographic convergence of the present results with the memory network proposed by Vincent et al. (J. Neurophysiol. 96:3517-3531, 2006) leads to the speculation that in our group of patients, rivastigmine specifically activates brain regions that are involved in memory functions, notably a key symptom in this degenerative disease.

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Light microscopy of thick biological samples, such as tissues, is often limited by aberrations caused by refractive index variations within the sample itself. This problem is particularly severe for live imaging, a field of great current excitement due to the development of inherently fluorescent proteins. We describe a method of removing such aberrations computationally by mapping the refractive index of the sample using differential interference contrast microscopy, modeling the aberrations by ray tracing through this index map, and using space-variant deconvolution to remove aberrations. This approach will open possibilities to study weakly labeled molecules in difficult-to-image live specimens.

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Functional magnetic resonance imaging (fMRI) is a tool for mapping brain function that utilizes neuronal activity-induced changes in blood oxygenation. An efficient three-dimensional fMRI method is presented for imaging brain activity on conventional, widely available, 1.5-T scanners, without additional hardware. This approach uses large magnetic susceptibility weighting based on the echo-shifting principle combined with multiple gradient echoes per excitation. Motor stimulation, induced by self-paced finger tapping, reliably produced significant signal increase in the hand region of the contralateral primary motor cortex in every subject tested.

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Recently, a 3-dimensional phantom that can provide a comprehensive, accurate and complete measurement of the geometric distortion in MRI has been developed. In this paper, a scheme for characterizing the measured geometric distortion using the 3-D phantom is described. In the proposed scheme, a number of quantitative measures are developed and used to characterize the geometric distortion. These measures encompass the overall and spatial aspects of the geometric distortion. Two specific types of volume of interest, rectangular parallelepipeds (including cubes) and spheres are considered in the proposed scheme. As an illustration, characterization of the geometric distortion in a Siemens 1.5T Sonata MRI system using the proposed scheme is presented. As shown, the proposed scheme provides a comprehensive assessment of the geometric distortion. The scheme can be potentially used as a standard procedure for the assessment of geometric distortion in MRI. (C) 2004 American Association of Physicists in Medicine.

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Left ventricular (LV) volumes have important prognostic implications in patients with chronic ischemic heart disease. We sought to examine the accuracy and reproducibility of real-time 3D echo (RT-3DE) compared to TI-201 single photon emission computed tomography (SPECT) and cardiac magnetic resonance imaging (MRI). Thirty (n = 30) patients (age 62±9 years, 23 men) with chronic ischemic heart disease underwent LV volume assessment with RT-3DE, SPECT, and MRI. Ano vel semi-automated border detection algorithmwas used by RT-3DE. End diastolic volumes (EDV) and end systolic volumes (ESV) measured by RT3DE and SPECT were compared to MRI as the standard of reference. RT-3DE and SPECT volumes showed excellent correlation with MRI (Table). Both RT- 3DE and SPECT underestimated LV volumes compared to MRI (ESV, SPECT 74±58 ml versus RT-3DE 95±48 ml versus MRI 96±54 ml); (EDV, SPECT 121±61 ml versus RT-3DE 169±61 ml versus MRI 179±56 ml). The degree of ESV underestimation with RT-3DE was not significant.

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PURPOSE. A methodology for noninvasively characterizing the three-dimensional (3-D) shape of the complete human eye is not currently available for research into ocular diseases that have a structural substrate, such as myopia. A novel application of a magnetic resonance imaging (MRI) acquisition and analysis technique is presented that, for the first time, allows the 3-D shape of the eye to be investigated fully. METHODS. The technique involves the acquisition of a T2-weighted MRI, which is optimized to reveal the fluid-filled chambers of the eye. Automatic segmentation and meshing algorithms generate a 3-D surface model, which can be shaded with morphologic parameters such as distance from the posterior corneal pole and deviation from sphericity. Full details of the method are illustrated with data from 14 eyes of seven individuals. The spatial accuracy of the calculated models is demonstrated by comparing the MRI-derived axial lengths with values measured in the same eyes using interferometry. RESULTS. The color-coded eye models showed substantial variation in the absolute size of the 14 eyes. Variations in the sphericity of the eyes were also evident, with some appearing approximately spherical whereas others were clearly oblate and one was slightly prolate. Nasal-temporal asymmetries were noted in some subjects. CONCLUSIONS. The MRI acquisition and analysis technique allows a novel way of examining 3-D ocular shape. The ability to stratify and analyze eye shape, ocular volume, and sphericity will further extend the understanding of which specific biometric parameters predispose emmetropic children subsequently to develop myopia. Copyright © Association for Research in Vision and Ophthalmology.

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To quantify changes in crystalline lens curvature, thickness, equatorial diameter, surface area, and volume during accommodation using a novel two-dimensional magnetic resonance imaging (MRI) paradigm to generate a complete three-dimensional crystalline lens surface model.

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This paper presents and demonstrates a method for using magnetic resonance imaging to measure local pressure of a fluid saturating a porous medium. The method is tested both in a static system of packed silica gel and in saturated sintered glass cylinders experiencing fluid flow. The fluid used contains 3% gas in the form of 3-μm average diameter gas filled 1,2-distearoyl-sn-glycero-3-phosphocholine (C18:0, MW: 790.16) liposomes suspended in 5% glycerol and 0.5% Methyl cellulose with water. Preliminary studies at 2.35 T demonstrate relative magnetic resonance signal changes of 20% per bar in bulk fluid for an echo time TE=40 ms, and 6-10% in consolidated porous media for TE=10 ms, over the range 0.8-1.8 bar for a spatial resolution of 0.1 mm3 and a temporal resolution of 30 s. The stability of this solution with relation to applied pressure and methods for improving sensitivity are discussed. © 2007 Elsevier Inc. All rights reserved.

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This dissertation establishes the foundation for a new 3-D visual interface integrating Magnetic Resonance Imaging (MRI) to Diffusion Tensor Imaging (DTI). The need for such an interface is critical for understanding brain dynamics, and for providing more accurate diagnosis of key brain dysfunctions in terms of neuronal connectivity. ^ This work involved two research fronts: (1) the development of new image processing and visualization techniques in order to accurately establish relational positioning of neuronal fiber tracts and key landmarks in 3-D brain atlases, and (2) the obligation to address the computational requirements such that the processing time is within the practical bounds of clinical settings. The system was evaluated using data from thirty patients and volunteers with the Brain Institute at Miami Children's Hospital. ^ Innovative visualization mechanisms allow for the first time white matter fiber tracts to be displayed alongside key anatomical structures within accurately registered 3-D semi-transparent images of the brain. ^ The segmentation algorithm is based on the calculation of mathematically-tuned thresholds and region-detection modules. The uniqueness of the algorithm is in its ability to perform fast and accurate segmentation of the ventricles. In contrast to the manual selection of the ventricles, which averaged over 12 minutes, the segmentation algorithm averaged less than 10 seconds in its execution. ^ The registration algorithm established searches and compares MR with DT images of the same subject, where derived correlation measures quantify the resulting accuracy. Overall, the images were 27% more correlated after registration, while an average of 1.5 seconds is all it took to execute the processes of registration, interpolation, and re-slicing of the images all at the same time and in all the given dimensions. ^ This interface was fully embedded into a fiber-tracking software system in order to establish an optimal research environment. This highly integrated 3-D visualization system reached a practical level that makes it ready for clinical deployment. ^

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Nanotechnology has revolutionised humanity's capability in building microscopic systems by manipulating materials on a molecular and atomic scale. Nan-osystems are becoming increasingly smaller and more complex from the chemical perspective which increases the demand for microscopic characterisation techniques. Among others, transmission electron microscopy (TEM) is an indispensable tool that is increasingly used to study the structures of nanosystems down to the molecular and atomic scale. However, despite the effectivity of this tool, it can only provide 2-dimensional projection (shadow) images of the 3D structure, leaving the 3-dimensional information hidden which can lead to incomplete or erroneous characterization. One very promising inspection method is Electron Tomography (ET), which is rapidly becoming an important tool to explore the 3D nano-world. ET provides (sub-)nanometer resolution in all three dimensions of the sample under investigation. However, the fidelity of the ET tomogram that is achieved by current ET reconstruction procedures remains a major challenge. This thesis addresses the assessment and advancement of electron tomographic methods to enable high-fidelity three-dimensional investigations. A quality assessment investigation was conducted to provide a quality quantitative analysis of the main established ET reconstruction algorithms and to study the influence of the experimental conditions on the quality of the reconstructed ET tomogram. Regular shaped nanoparticles were used as a ground-truth for this study. It is concluded that the fidelity of the post-reconstruction quantitative analysis and segmentation is limited, mainly by the fidelity of the reconstructed ET tomogram. This motivates the development of an improved tomographic reconstruction process. In this thesis, a novel ET method was proposed, named dictionary learning electron tomography (DLET). DLET is based on the recent mathematical theorem of compressed sensing (CS) which employs the sparsity of ET tomograms to enable accurate reconstruction from undersampled (S)TEM tilt series. DLET learns the sparsifying transform (dictionary) in an adaptive way and reconstructs the tomogram simultaneously from highly undersampled tilt series. In this method, the sparsity is applied on overlapping image patches favouring local structures. Furthermore, the dictionary is adapted to the specific tomogram instance, thereby favouring better sparsity and consequently higher quality reconstructions. The reconstruction algorithm is based on an alternating procedure that learns the sparsifying dictionary and employs it to remove artifacts and noise in one step, and then restores the tomogram data in the other step. Simulation and real ET experiments of several morphologies are performed with a variety of setups. Reconstruction results validate its efficiency in both noiseless and noisy cases and show that it yields an improved reconstruction quality with fast convergence. The proposed method enables the recovery of high-fidelity information without the need to worry about what sparsifying transform to select or whether the images used strictly follow the pre-conditions of a certain transform (e.g. strictly piecewise constant for Total Variation minimisation). This can also avoid artifacts that can be introduced by specific sparsifying transforms (e.g. the staircase artifacts the may result when using Total Variation minimisation). Moreover, this thesis shows how reliable elementally sensitive tomography using EELS is possible with the aid of both appropriate use of Dual electron energy loss spectroscopy (DualEELS) and the DLET compressed sensing algorithm to make the best use of the limited data volume and signal to noise inherent in core-loss electron energy loss spectroscopy (EELS) from nanoparticles of an industrially important material. Taken together, the results presented in this thesis demonstrates how high-fidelity ET reconstructions can be achieved using a compressed sensing approach.