892 resultados para subtraction technique
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Objectives: The aim of this study was to compare two methods for the evaluation of periapical lesion changes following endodontic therapy (digital subtraction technique and morphometric analysis) by outlining the radiolucent area.Methods: 13 human anterior teeth with pulp necrosis and chronic periapical lesions were used. Periapical radiographs were taken immediately after endodontic therapy (0) and then 2 months, 4 months and 6 months post treatment, using an intraoral radiographic film holder stabilized with impression material. The films were processed in a standard manner and the digitized images were submitted to digital subtraction using Adobe Photoshop 6.0. New bone formation or bone resorption areas were then measured. In the morphometric analysis, the periapical lesions were outlined using VixWin 2000 and the area (in square millimetres) was recorded. The obtained data were submitted to agreement analysis for comparison of the two techniques.Results: There was no correlation between the areas of radiographic changes detected by digital subtraction and periapical lesion outline (r=0.02-0.45). The new bone formation areas observed by digital subtraction presented higher values, with bone changes being especially evident in the 2 month follow-up radiographs, which suggests a higher sensitivity for this method.Conclusions: Both methods are suitable for the evaluation of periapical lesion changes, but the digital subtraction technique is more sensitive for detecting radiographic periapical changes. Dentomaxillofacial Radiology (2009) 38, 438-444. doi: 10.1259/dmfr/53304677
Local re-inversion coronary MR angiography: arterial spin-labeling without the need for subtraction.
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PURPOSE: To implement a double-inversion bright-blood coronary MR angiography sequence using a cylindrical re-inversion prepulse for selective visualization of the coronary arteries. MATERIALS AND METHODS: Local re-inversion bright-blood magnetization preparation was implemented using a nonselective inversion followed by a cylindrical aortic re-inversion prepulse. After an inversion delay that allows for in-flow of the labeled blood-pool into the coronary arteries, three-dimensional radial steady-state free-precession (SSFP) imaging (repetition/echo time, 7.2/3.6 ms; flip angle, 120 degrees, 16 profiles per RR interval; field of view, 360 mm; matrix, 512, twelve 3-mm slices) is performed. Coronary MR angiography was performed in three healthy volunteers and in one patient on a commercial 1.5 Tesla whole-body MR System. RESULTS: In all subjects, coronary arteries were selectively visualized with positive contrast. In addition, a middle-grade stenosis of the proximal right coronary artery was seen in one patient. CONCLUSION: A novel T1 contrast-enhancement strategy is presented for selective visualization of the coronary arteries without extrinsic contrast medium application. In comparison to former arterial spin-labeling schemes, the proposed magnetization preparation obviates the need for a second data set and subtraction.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.
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In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatent of Parkinson's disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different registration algorithms and to evaluate their ability to locate the STN automatically. Using this scheme we can evaluate the expert variability against the error of the algorithms and we demonstrate that automatic STN location is possible and as accurate as the methods currently used.
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Three-dimensional imaging and quantification of myocardial function are essential steps in the evaluation of cardiac disease. We propose a tagged magnetic resonance imaging methodology called zHARP that encodes and automatically tracks myocardial displacement in three dimensions. Unlike other motion encoding techniques, zHARP encodes both in-plane and through-plane motion in a single image plane without affecting the acquisition speed. Postprocessing unravels this encoding in order to directly track the 3-D displacement of every point within the image plane throughout an entire image sequence. Experimental results include a phantom validation experiment, which compares zHARP to phase contrast imaging, and an in vivo study of a normal human volunteer. Results demonstrate that the simultaneous extraction of in-plane and through-plane displacements from tagged images is feasible.
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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.
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In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatent of Parkinson's disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different registration algorithms and to evaluate their ability to locate the STN automatically. Using this scheme we can evaluate the expert variability against the error of the algorithms and we demonstrate that automatic STN location is possible and as accurate as the methods currently used.
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New representations and efficient calculation methods are derived for the problem of propagation from an infinite regularly spaced array of coherent line sources above a homogeneous impedance plane, and for the Green's function for sound propagation in the canyon formed by two infinitely high, parallel rigid or sound soft walls and an impedance ground surface. The infinite sum of source contributions is replaced by a finite sum and the remainder is expressed as a Laplace-type integral. A pole subtraction technique is used to remove poles in the integrand which lie near the path of integration, obtaining a smooth integrand, more suitable for numerical integration, and a specific numerical integration method is proposed. Numerical experiments show highly accurate results across the frequency spectrum for a range of ground surface types. It is expected that the methods proposed will prove useful in boundary element modeling of noise propagation in canyon streets and in ducts, and for problems of scattering by periodic surfaces.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Biopatologia Bucal - ICT
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A nonlinear viscoelastic image registration algorithm based on the demons paradigm and incorporating inverse consistent constraint (ICC) is implemented. An inverse consistent and symmetric cost function using mutual information (MI) as a similarity measure is employed. The cost function also includes regularization of transformation and inverse consistent error (ICE). The uncertainties in balancing various terms in the cost function are avoided by alternatively minimizing the similarity measure, the regularization of the transformation, and the ICE terms. The diffeomorphism of registration for preventing folding and/or tearing in the deformation is achieved by the composition scheme. The quality of image registration is first demonstrated by constructing brain atlas from 20 adult brains (age range 30-60). It is shown that with this registration technique: (1) the Jacobian determinant is positive for all voxels and (2) the average ICE is around 0.004 voxels with a maximum value below 0.1 voxels. Further, the deformation-based segmentation on Internet Brain Segmentation Repository, a publicly available dataset, has yielded high Dice similarity index (DSI) of 94.7% for the cerebellum and 74.7% for the hippocampus, attesting to the quality of our registration method.