958 resultados para Magnetic resonance image
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The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.
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Medical imaging technology and applications are continuously evolving, dealing with images of increasing spatial and temporal resolutions, which allow easier and more accurate medical diagnosis. However, this increase in resolution demands a growing amount of data to be stored and transmitted. Despite the high coding efficiency achieved by the most recent image and video coding standards in lossy compression, they are not well suited for quality-critical medical image compression where either near-lossless or lossless coding is required. In this dissertation, two different approaches to improve lossless coding of volumetric medical images, such as Magnetic Resonance and Computed Tomography, were studied and implemented using the latest standard High Efficiency Video Encoder (HEVC). In a first approach, the use of geometric transformations to perform inter-slice prediction was investigated. For the second approach, a pixel-wise prediction technique, based on Least-Squares prediction, that exploits inter-slice redundancy was proposed to extend the current HEVC lossless tools. Experimental results show a bitrate reduction between 45% and 49%, when compared with DICOM recommended encoders, and 13.7% when compared with standard HEVC.
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PURPOSE: The goal of the present study was to use a three-dimensional (3D) gradient echo volume in combination with a fat-selective excitation as a 3D motion navigator (3D FatNav) for retrospective correction of microscopic head motion during high-resolution 3D structural scans of extended duration. The fat excitation leads to a 3D image that is itself sparse, allowing high parallel imaging acceleration factors - with the additional advantage of a minimal disturbance of the water signal used for the host sequence. METHODS: A 3D FatNav was inserted into two structural protocols: an inversion-prepared gradient echo at 0.33 × 0.33 × 1.00 mm resolution and a turbo spin echo at 600 μm isotropic resolution. RESULTS: Motion estimation was possible with high precision, allowing retrospective motion correction to yield clear improvements in image quality, especially in the conspicuity of very small blood vessels. CONCLUSION: The highly accelerated 3D FatNav allowed motion correction with noticeable improvements in image quality, even for head motion which was small compared with the voxel dimensions of the host sequence. Magn Reson Med 75:1030-1039, 2016. © 2015 Wiley Periodicals, Inc.
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To investigate the degree of T2 relaxometry changes over time in groups of patients with familial mesial temporal lobe epilepsy (FMTLE) and asymptomatic relatives. We conducted both cross-sectional and longitudinal analyses of T2 relaxometry with Aftervoxel, an in-house software for medical image visualization. The cross-sectional study included 35 subjects (26 with FMTLE and 9 asymptomatic relatives) and 40 controls; the longitudinal study was composed of 30 subjects (21 with FMTLE and 9 asymptomatic relatives; the mean time interval of MRIs was 4.4 ± 1.5 years) and 16 controls. To increase the size of our groups of patients and relatives, we combined data acquired in 2 scanners (2T and 3T) and obtained z-scores using their respective controls. General linear model on SPSS21® was used for statistical analysis. In the cross-sectional analysis, elevated T2 relaxometry was identified for subjects with seizures and intermediate values for asymptomatic relatives compared to controls. Subjects with MRI signs of hippocampal sclerosis presented elevated T2 relaxometry in the ipsilateral hippocampus, while patients and asymptomatic relatives with normal MRI presented elevated T2 values in the right hippocampus. The longitudinal analysis revealed a significant increase in T2 relaxometry for the ipsilateral hippocampus exclusively in patients with seizures. The longitudinal increase of T2 signal in patients with seizures suggests the existence of an interaction between ongoing seizures and the underlying pathology, causing progressive damage to the hippocampus. The identification of elevated T2 relaxometry in asymptomatic relatives and in patients with normal MRI suggests that genetic factors may be involved in the development of some mild hippocampal abnormalities in FMTLE.
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Primary craniocervical dystonia (CCD) is generally attributed to functional abnormalities in the cortico-striato-pallido-thalamocortical loops, but cerebellar pathways have also been implicated in neuroimaging studies. Hence, our purpose was to perform a volumetric evaluation of the infratentorial structures in CCD. We compared 35 DYT1/DYT6 negative patients with CCD and 35 healthy controls. Cerebellar volume was evaluated using manual volumetry (DISPLAY software) and infratentorial volume by voxel based morphometry of gray matter (GM) segments derived from T1 weighted 3 T MRI using the SUIT tool (SPM8/Dartel). We used t-tests to compare infratentorial volumes between groups. Cerebellar volume was (1.14 ± 0.17) × 10(2) cm(3) for controls and (1.13 ± 0.14) × 10(2) cm(3) for patients; p = 0.74. VBM demonstrated GM increase in the left I-IV cerebellar lobules and GM decrease in the left lobules VI and Crus I and in the right lobules VI, Crus I and VIIIb. In a secondary analysis, VBM demonstrated GM increase also in the brainstem, mostly in the pons. While gray matter increase is observed in the anterior lobe of the cerebellum and in the brainstem, the atrophy is concentrated in the posterior lobe of the cerebellum, demonstrating a differential pattern of infratentorial involvement in CCD. This study shows subtle structural abnormalities of the cerebellum and brainstem in primary CCD.
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The search for an Alzheimer's disease (AD) biomarker is one of the most relevant contemporary research topics due to the high prevalence and social costs of the disease. Functional connectivity (FC) of the default mode network (DMN) is a plausible candidate for such a biomarker. We evaluated 22 patients with mild AD and 26 age- and gender-matched healthy controls. All subjects underwent resting functional magnetic resonance imaging (fMRI) in a 3.0 T scanner. To identify the DMN, seed-based FC of the posterior cingulate was calculated. We also measured the sensitivity/specificity of the method, and verified a correlation with cognitive performance. We found a significant difference between patients with mild AD and controls in average z-scores: DMN, whole cortical positive (WCP) and absolute values. DMN individual values showed a sensitivity of 77.3% and specificity of 70%. DMN and WCP values were correlated to global cognition and episodic memory performance. We showed that individual measures of DMN connectivity could be considered a promising method to differentiate AD, even at an early phase, from normal aging. Further studies with larger numbers of participants, as well as validation of normal values, are needed for more definitive conclusions.
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The authors report the study of eight children with diskitis diagnosed through clinical, neurogical and orthopedic evaluation. The evidence of self limiting inflammation or infection of the intervertebral disk space and of soft tissue were avaliable by image studies. Findings with routine roentgenograms, computed tomography and magnetic resonance imaging are discussed.
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A imagem por ressonância magnética (IRM) é o método de diagnóstico por imagem não invasivo mais sensível para avaliar as partes moles, particularmente o encéfalo, porém trata-se de uma técnica onerosa. O método fundamenta-se no fenômeno da ressonância magnética nuclear que ocorre quando núcleos atômicos com propriedades magnéticas presentes no corpo são submetidos a um campo magnético intenso, sendo posteriormente excitados por energia de radiofrequência e gerando, por sua vez, um sinal de onda de radiofrequência capaz de ser captado por uma antena receptora, passando por um processo matemático, chamado Transformada de Fourier, para posterior formação da imagem. Esse estudo objetivou realizar 10 exames completos da cabeça em cadáveres de cães normais à IRM e confeccionar um Atlas com as estruturas identificadas. As imagens foram adquiridas em um aparelho de ressonância magnética Gyroscan S15/HP Philips com campo magnético de 1,5Tesla. Os cadáveres foram posicionados com a cabeça no interior de uma bobina de cabeça humana e foram submetidos a cortes iniciais sagitais a partir de onde se planejou os cortes transversais e dorsais nas sequências de pulso spin-eco T1, T2 e DP. Em T1 utilizou-se TR=400ms e TE=30ms, T2 utilizou-se TR=2000ms e TE=80ms e na DP utilizou-se TR=2000ms e TE=30ms. A espessura do corte foi de 4mm, o número de médias foi igual a 2, a matriz foi de 256x256, o fator foi igual a 1,0 e o campo de visão foi de 14cm. A duração do exame completo da cabeça foi de 74,5minutos. As imagens obtidas com as sequências utilizadas e com a bobina de cabeça humana foram de boa qualidade. Em T1 a gordura tornou-se hiperintensa e o líquido hipointenso. Em T2 a gordura ficou menos hiperintensa e o líquido hiperintenso. A cortical óssea e o ar foram hipointensos em todas as sequências utilizadas devido a baixa densidade de prótons. A sequência DP mostrou o melhor contraste entre a substância branca e cinzenta quando comparada a T2 e a T1. T2 evidenciou o líquido cefalorraquidiano tornando possível a distinção dos sulcos e giros cerebrais. Através do exame de IRM foi possível, pelo contraste, identificar as estruturas ósseas componentes da arquitetura da região, músculos, grandes vasos venosos e arteriais e estruturas do sistema nervoso central, além de elementos do sistema digestório, respiratório e estruturas dos olhos entre outras. Nesse estudo as IRM adquiridas nas sequências T1, DP e T2 foram complementares para o estudo dos aspectos anatômicos da cabeça de cães demonstrando-os com riqueza de detalhes. O tempo requerido para o exame completo da cabeça é compátivel para uso em animais vivos desde que devidamente anestesiados e controlados. Os resultados obtidos por esse trabalho abrem caminho em nosso meio, para o estudo de animais vivos e para o início da investigação de doenças, principalmente as de origem neurológica, visto ser esta técnica excelente para a visibilização do encéfalo.
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In recent years, magnetic nanoparticles have been studied due to their potential applications as magnetic carriers in biomedical area. These materials have been increasingly exploited as efficient delivery vectors, leading to opportunities of use as magnetic resonance imaging (MRI) agents, mediators of hyperthermia cancer treatment and in targeted therapies. Much attention has been also focused on ""smart"" polymers, which are able to respond to environmental changes, such as changes in the temperature and pH. In this context, this article reviews the state-of-the art in stimuli-responsive magnetic systems for biomedical applications. The paper describes different types of stimuli-sensitive systems, mainly temperature- and pH sensitive polymers, the combination of this characteristic with magnetic properties and, finally, it gives an account of their preparation methods. The article also discusses the main in vivo biomedical applications of such materials. A survey of the recent literature on various stimuli-responsive magnetic gels in biomedical applications is also included. (C) 2010 Elsevier B.V. All rights reserved.
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This work discusses the determination of the breathing patterns in time sequence of images obtained from magnetic resonance (MR) and their use in the temporal registration of coronal and sagittal images. The registration is made without the use of any triggering information and any special gas to enhance the contrast. The temporal sequences of images are acquired in free breathing. The real movement of the lung has never been seen directly, as it is totally dependent on its surrounding muscles and collapses without them. The visualization of the lung in motion is an actual topic of research in medicine. The lung movement is not periodic and it is susceptible to variations in the degree of respiration. Compared to computerized tomography (CT), MR imaging involves longer acquisition times and it is preferable because it does not involve radiation. As coronal and sagittal sequences of images are orthogonal to each other, their intersection corresponds to a segment in the three-dimensional space. The registration is based on the analysis of this intersection segment. A time sequence of this intersection segment can be stacked, defining a two-dimension spatio-temporal (2DST) image. The algorithm proposed in this work can detect asynchronous movements of the internal lung structures and lung surrounding organs. It is assumed that the diaphragmatic movement is the principal movement and all the lung structures move almost synchronously. The synchronization is performed through a pattern named respiratory function. This pattern is obtained by processing a 2DST image. An interval Hough transform algorithm searches for synchronized movements with the respiratory function. A greedy active contour algorithm adjusts small discrepancies originated by asynchronous movements in the respiratory patterns. The output is a set of respiratory patterns. Finally, the composition of coronal and sagittal image pairs that are in the same breathing phase is realized by comparing of respiratory patterns originated from diaphragmatic and upper boundary surfaces. When available, the respiratory patterns associated to lung internal structures are also used. The results of the proposed method are compared with the pixel-by-pixel comparison method. The proposed method increases the number of registered pairs representing composed images and allows an easy check of the breathing phase. (C) 2010 Elsevier Ltd. All rights reserved.
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Intravascular ultrasound (IVUS) image segmentation can provide more detailed vessel and plaque information, resulting in better diagnostics, evaluation and therapy planning. A novel automatic segmentation proposal is described herein; the method relies on a binary morphological object reconstruction to segment the coronary wall in IVUS images. First, a preprocessing followed by a feature extraction block are performed, allowing for the desired information to be extracted. Afterward, binary versions of the desired objects are reconstructed, and their contours are extracted to segment the image. The effectiveness is demonstrated by segmenting 1300 images, in which the outcomes had a strong correlation to their corresponding gold standard. Moreover, the results were also corroborated statistically by having as high as 92.72% and 91.9% of true positive area fraction for the lumen and media adventitia border, respectively. In addition, this approach can be adapted easily and applied to other related modalities, such as intravascular optical coherence tomography and intravascular magnetic resonance imaging. (E-mail: matheuscardosomg@hotmail.com) (C) 2011 World Federation for Ultrasound in Medicine & Biology.
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With the advent of functional neuroimaging techniques, in particular functional magnetic resonance imaging (fMRI), we have gained greater insight into the neural correlates of visuospatial function. However, it may not always be easy to identify the cerebral regions most specifically associated with performance on a given task. One approach is to examine the quantitative relationships between regional activation and behavioral performance measures. In the present study, we investigated the functional neuroanatomy of two different visuospatial processing tasks, judgement of line orientation and mental rotation. Twenty-four normal participants were scanned with fMRI using blocked periodic designs for experimental task presentation. Accuracy and reaction time (RT) to each trial of both activation and baseline conditions in each experiment was recorded. Both experiments activated dorsal and ventral visual cortical areas as well as dorsolateral prefrontal cortex. More regionally specific associations with task performance were identified by estimating the association between (sinusoidal) power of functional response and mean RT to the activation condition; a permutation test based on spatial statistics was used for inference. There was significant behavioral-physiological association in right ventral extrastriate cortex for the line orientation task and in bilateral (predominantly right) superior parietal lobule for the mental rotation task. Comparable associations were not found between power of response and RT to the baseline conditions of the tasks. These data suggest that one region in a neurocognitive network may be most strongly associated with behavioral performance and this may be regarded as the computationally least efficient or rate-limiting node of the network.
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This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood and adult-onset schizophrenia, bipolar disorder, attention-deficit/ hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages. (C) 2004 Published by Elsevier Inc.
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Resting state functional magnetic resonance imaging (fMRI) reveals a distinct network of correlated brain function representing a default mode state of the human brain The underlying structural basis of this functional connectivity pattern is still widely unexplored We combined fractional anisotropy measures of fiber tract integrity derived from diffusion tensor imaging (DTI) and resting state fMRI data obtained at 3 Tesla from 20 healthy elderly subjects (56 to 83 years of age) to determine white matter microstructure e 7 underlying default mode connectivity We hypothesized that the functional connectivity between the posterior cingulate and hippocampus from resting state fMRI data Would be associated with the white matter microstructure in the cingulate bundle and fiber tracts connecting posterior cingulate gyrus With lateral temporal lobes, medial temporal lobes, and precuneus This was demonstrated at the p<0001 level using a voxel-based multivariate analysis of covariance (MANCOVA) approach In addition, we used a data-driven technique of joint independent component analysis (ICA) that uncovers spatial pattern that are linked across modalities. It revealed a pattern of white matter tracts including cingulate bundle and associated fiber tracts resembling the findings from the hypothesis-driven analysis and was linked to the pattern of default mode network (DMN) connectivity in the resting state fMRI data Out findings support the notion that the functional connectivity between the posterior cingulate and hippocampus and the functional connectivity across the entire DMN is based oil distinct pattern of anatomical connectivity within the cerebral white matter (C) 2009 Elsevier Inc All rights reserved
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OBJECTIVE To examine cortical thickness and volumetric changes in the cortex of patients with polymicrogyria, using an automated image analysis algorithm. METHODS Cortical thickness of patients with polymicrogyria was measured using magnetic resonance imaging (MRI) cortical surface-based analysis and compared with age-and sex-matched healthy subjects. We studied 3 patients with disorder of cortical development (DCD), classified as polymicrogyria, and 15 controls. Two experienced neuroradiologists performed a conventional visual assessment of the MRIs. The same data were analyzed using an automated algorithm for tissue segmentation and classification. Group and individual average maps of cortical thickness differences were produced by cortical surface-based statistical analysis. RESULTS Patients with polymicrogyria showed increased thickness of the cortex in the same areas identified as abnormal by radiologists. We also identified a reduction in the volume and thickness of cortex within additional areas of apparently normal cortex relative to controls. CONCLUSIONS Our findings indicate that there may be regions of reduced cortical thickness, which appear normal from radiological analysis, in the cortex of patients with polymicrogyria. This finding suggests that alterations in neuronal migration may have an impact in the cortical formation of the cortical areas that are visually normal. These areas are associated or occur concurrently with polymicrogyria.