188 resultados para 3D acquisitions registration
Resumo:
The authors compared radial steady-state free precession (SSFP) coronary magnetic resonance (MR) angiography, cartesian k-space sampling SSFP coronary MR angiography, and gradient-echo coronary MR angiography in 16 healthy adults and four pilot study patients. Standard gradient-echo MR imaging with a T2 preparatory pulse and cartesian k-space sampling was the reference technique. Image quality was compared by using subjective motion artifact level and objective contrast-to-noise ratio and vessel sharpness. Radial SSFP, compared with cartesian SSFP and gradient-echo MR angiography, resulted in reduced motion artifacts and superior vessel sharpness. Cartesian SSFP resulted in increased motion artifacts (P <.05). Contrast-to-noise ratio with radial SSFP was lower than that with cartesian SSFP and similar to that with the reference technique. Radial SSFP coronary MR angiography appears preferable because of improved definition of vessel borders.
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This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.
Resumo:
During conventional x-ray coronary angiography, multiple projections of the coronary arteries are acquired to define coronary anatomy precisely. Due to time constraints, coronary magnetic resonance angiography (MRA) usually provides only one or two views of the major coronary vessels. A coronary MRA approach that allowed for reconstruction of arbitrary isotropic orientations might therefore be desirable. The purpose of the study was to develop a three-dimensional (3D) coronary MRA technique with isotropic image resolution in a relatively short scanning time that allows for reconstruction of arbitrary views of the coronary arteries without constraints given by anisotropic voxel size. Eight healthy adult subjects were examined using a real-time navigator-gated and corrected free-breathing interleaved echoplanar (TFE-EPI) 3D-MRA sequence. Two 3D datasets were acquired for the left and right coronary systems in each subject, one with anisotropic (1.0 x 1.5 x 3.0 mm, 10 slices) and one with "near" isotropic (1.0 x 1.5 x 1.0 mm, 30 slices) image resolution. All other imaging parameters were maintained. In all cases, the entire left main (LM) and extensive portions of the left anterior descending (LAD) and the right coronary artery (RCA) were visualized. Objective assessment of coronary vessel sharpness was similar (41% +/- 5% vs. 42% +/- 5%; P = NS) between in-plane and through-plane views with "isotropic" voxel size but differed (32% +/- 7% vs. 23% +/- 4%; P < 0.001) with nonisotropic voxel size. In reconstructed views oriented in the through-plane direction, the vessel border was 86% more defined (P < 0.01) for isotropic compared with anisotropic images. A smaller (30%; P < 0.001) improvement was seen for in-plane reconstructions. Vessel diameter measurements were view independent (2.81 +/- 0.45 mm vs. 2.66 +/- 0.52 mm; P = NS) for isotropic, but differed (2.71 +/- 0.51 mm vs. 3.30 +/- 0.38 mm; P < 0.001) between anisotropic views. Average scanning time was 2:31 +/- 0:57 minutes for anisotropic and 7:11 +/- 3:02 minutes for isotropic image resolution (P < 0.001). We present a new approach for "near" isotropic 3D coronary artery imaging, which allows for reconstruction of arbitrary views of the coronary arteries. The good delineation of the coronary arteries in all views suggests that isotropic 3D coronary MRA might be a preferred technique for the assessment of coronary disease, although at the expense of prolonged scan times. Comparative studies with conventional x-ray angiography are needed to investigate the clinical utility of the isotropic strategy.
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In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.
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Multi-centre data repositories like the Alzheimer's Disease Neuroimaging Initiative (ADNI) offer a unique research platform, but pose questions concerning comparability of results when using a range of imaging protocols and data processing algorithms. The variability is mainly due to the non-quantitative character of the widely used structural T1-weighted magnetic resonance (MR) images. Although the stability of the main effect of Alzheimer's disease (AD) on brain structure across platforms and field strength has been addressed in previous studies using multi-site MR images, there are only sparse empirically-based recommendations for processing and analysis of pooled multi-centre structural MR data acquired at different magnetic field strengths (MFS). Aiming to minimise potential systematic bias when using ADNI data we investigate the specific contributions of spatial registration strategies and the impact of MFS on voxel-based morphometry in AD. We perform a whole-brain analysis within the framework of Statistical Parametric Mapping, testing for main effects of various diffeomorphic spatial registration strategies, of MFS and their interaction with disease status. Beyond the confirmation of medial temporal lobe volume loss in AD, we detect a significant impact of spatial registration strategy on estimation of AD related atrophy. Additionally, we report a significant effect of MFS on the assessment of brain anatomy (i) in the cerebellum, (ii) the precentral gyrus and (iii) the thalamus bilaterally, showing no interaction with the disease status. We provide empirical evidence in support of pooling data in multi-centre VBM studies irrespective of disease status or MFS.
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Relaxation rates provide important information about tissue microstructure. Multi-parameter mapping (MPM) estimates multiple relaxation parameters from multi-echo FLASH acquisitions with different basic contrasts, i.e., proton density (PD), T1 or magnetization transfer (MT) weighting. Motion can particularly affect maps of the apparent transverse relaxation rate R2(*), which are derived from the signal of PD-weighted images acquired at different echo times. To address the motion artifacts, we introduce ESTATICS, which robustly estimates R2(*) from images even when acquired with different basic contrasts. ESTATICS extends the fitted signal model to account for inherent contrast differences in the PDw, T1w and MTw images. The fit was implemented as a conventional ordinary least squares optimization and as a robust fit with a small or large confidence interval. These three different implementations of ESTATICS were tested on data affected by severe motion artifacts and data with no prominent motion artifacts as determined by visual assessment or fast optical motion tracking. ESTATICS improved the quality of the R2(*) maps and reduced the coefficient of variation for both types of data-with average reductions of 30% when severe motion artifacts were present. ESTATICS can be applied to any protocol comprised of multiple 2D/3D multi-echo FLASH acquisitions as used in the general research and clinical setting.
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With the dramatic increase in the volume of experimental results in every domain of life sciences, assembling pertinent data and combining information from different fields has become a challenge. Information is dispersed over numerous specialized databases and is presented in many different formats. Rapid access to experiment-based information about well-characterized proteins helps predict the function of uncharacterized proteins identified by large-scale sequencing. In this context, universal knowledgebases play essential roles in providing access to data from complementary types of experiments and serving as hubs with cross-references to many specialized databases. This review outlines how the value of experimental data is optimized by combining high-quality protein sequences with complementary experimental results, including information derived from protein 3D-structures, using as an example the UniProt knowledgebase (UniProtKB) and the tools and links provided on its website ( http://www.uniprot.org/ ). It also evokes precautions that are necessary for successful predictions and extrapolations.
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In this paper, we present the segmentation of the headand neck lymph node regions using a new active contourbased atlas registration model. We propose to segment thelymph node regions without directly including them in theatlas registration process; instead, they are segmentedusing the dense deformation field computed from theregistration of the atlas structures with distinctboundaries. This approach results in robust and accuratesegmentation of the lymph node regions even in thepresence of significant anatomical variations between theatlas-image and the patient's image to be segmented. Wealso present a quantitative evaluation of lymph noderegions segmentation using various statistical as well asgeometrical metrics: sensitivity, specificity, dicesimilarity coefficient and Hausdorff distance. Acomparison of the proposed method with two other state ofthe art methods is presented. The robustness of theproposed method to the atlas selection, in segmenting thelymph node regions, is also evaluated.
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In this study we propose an evaluation of the angular effects altering the spectral response of the land-cover over multi-angle remote sensing image acquisitions. The shift in the statistical distribution of the pixels observed in an in-track sequence of WorldView-2 images is analyzed by means of a kernel-based measure of distance between probability distributions. Afterwards, the portability of supervised classifiers across the sequence is investigated by looking at the evolution of the classification accuracy with respect to the changing observation angle. In this context, the efficiency of various physically and statistically based preprocessing methods in obtaining angle-invariant data spaces is compared and possible synergies are discussed.
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A cardiac-triggered, free-breathing, 3D balanced FFE projection renal MR angiography (MRA) technique with a 2D pencil beam aortic labeling pulse for selective aortic spin tagging was developed. For respiratory motion artifact suppression during free breathing, a prospective real-time navigator was implemented for renal MRA. Images obtained with the new approach were compared with standard contrast-enhanced (CE) 3D breath-hold MRA in seven swine. Signal properties and vessel visualization were analyzed. With the presented technique, high-resolution, high-contrast renal projection MRA with superior vessel length visualization (including a greater visible number of distal branches of the renal arteries) compared to standard breath-hold CE-MRA was obtained. The present results warrant clinical studies in patients with renal artery disease.
Resumo:
Diffusion-weighting in magnetic resonance imaging (MRI) increases the sensitivity to molecular Brownian motion, providing insight in the micro-environment of the underlying tissue types and structures. At the same time, the diffusion weighting renders the scans sensitive to other motion, including bulk patient motion. Typically, several image volumes are needed to extract diffusion information, inducing also inter-volume motion susceptibility. Bulk motion is more likely during long acquisitions, as they appear in diffusion tensor, diffusion spectrum and q-ball imaging. Image registration methods are successfully used to correct for bulk motion in other MRI time series, but their performance in diffusion-weighted MRI is limited since diffusion weighting introduces strong signal and contrast changes between serial image volumes. In this work, we combine the capability of free induction decay (FID) navigators, providing information on object motion, with image registration methodology to prospectively--or optionally retrospectively--correct for motion in diffusion imaging of the human brain. Eight healthy subjects were instructed to perform small-scale voluntary head motion during clinical diffusion tensor imaging acquisitions. The implemented motion detection based on FID navigator signals is processed in real-time and provided an excellent detection performance of voluntary motion patterns even at a sub-millimetre scale (sensitivity≥92%, specificity>98%). Motion detection triggered an additional image volume acquisition with b=0 s/mm2 which was subsequently co-registered to a reference volume. In the prospective correction scenario, the calculated motion-parameters were applied to perform a real-time update of the gradient coordinate system to correct for the head movement. Quantitative analysis revealed that the motion correction implementation is capable to correct head motion in diffusion-weighted MRI to a level comparable to scans without voluntary head motion. The results indicate the potential of this method to improve image quality in diffusion-weighted MRI, a concept that can also be applied when highest diffusion weightings are performed.
Resumo:
PURPOSE: In the present study, the impact of the two different fat suppression techniques was investigated for free breathing 3D spiral coronary magnetic resonance angiography (MRA). As the coronary arteries are embedded in epicardial fat and are adjacent to myocardial tissue, magnetization preparation such as T(2)-preparation and fat suppression is essential for coronary discrimination. MATERIALS AND METHODS: Fat-signal suppression in three-dimensional (3D) thin- slab coronary MRA based on a spiral k-space data acquisition can either be achieved by signal pre-saturation using a spectrally selective inversion recovery pre-pulse or by spectral-spatial excitation. In the present study, the performance of the two different approaches was studied in healthy subjects. RESULTS: No significant objective or subjective difference was found between the two fat suppression approaches. CONCLUSION: Spectral pre-saturation seems preferred for coronary MRA applications due to the ease of implementation and the shorter cardiac acquisition window.