989 resultados para multilevel optimization multigrid PDE image restoration


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A branch and bound algorithm is proposed to solve the [image omitted]-norm model reduction problem for continuous and discrete-time linear systems, with convergence to the global optimum in a finite time. The lower and upper bounds in the optimization procedure are described by linear matrix inequalities (LMI). Also proposed are two methods with which to reduce the convergence time of the branch and bound algorithm: the first one uses the Hankel singular values as a sufficient condition to stop the algorithm, providing to the method a fast convergence to the global optimum. The second one assumes that the reduced model is in the controllable or observable canonical form. The [image omitted]-norm of the error between the original model and the reduced model is considered. Examples illustrate the application of the proposed method.

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The efficiency in image classification tasks can be improved using combined information provided by several sources, such as shape, color, and texture visual properties. Although many works proposed to combine different feature vectors, we model the descriptor combination as an optimization problem to be addressed by evolutionary-based techniques, which compute distances between samples that maximize their separability in the feature space. The robustness of the proposed technique is assessed by the Optimum-Path Forest classifier. Experiments showed that the proposed methodology can outperform individual information provided by single descriptors in well-known public datasets. © 2012 IEEE.

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The daily-to-day of medical practice is marked by a constant search for an accurate diagnosis and therapeutic assessment. For this purpose the doctor serves up a wide variety of imaging techniques, however, the methods using ionizing radiation still the most widely used because it is considered cheaper and above all very efficient when used with control and quality. The optimization of the risk-benefit ratio is considered a major breakthrough in relation to conventional radiology, though this is not the reality of computing and digital radiology, where Brazil has not established standards and protocols for this purpose. This work aims to optimize computational chest radiographs (anterior-posterior projection-AP). To achieve this objective were used a homogeneous phantoms that simulate the characteristics of absorption and scattering of radiation close to the chest of a patient standard. Another factor studied was the subjective evaluation of image quality, carried out by visual grading assessment (VGA) by specialists in radiology, using an anthropomorphic phantom to identify the best image for a particular pathology (fracture or pneumonia). Quantifying the corresponding images indicated by the radiologist was performed from the quantification of physical parameters (Detective Quantum Efficiency - DQE, Modulation Transfer Function - MTF and Noise Power Spectrum - NPS) using the software MatLab®. © 2013 Springer-Verlag.

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Objective: To compare dental plaster model (DPM) and cone-beam computed tomography (CBCT) in the measurement of the dental arches, and investigate whether CBCT image artifacts compromise the reliability of such measurements.Materials and Methods: Twenty patients were divided into two groups based on the presence or absence of metallic restorations in the posterior teeth. Both dental arches of the patients were scanned with the CBCT unit i-CAT, and DPMs were obtained. Two examiners obtained eight arch measurements on the CBCT images and DPMs and repeated this procedure 15 days later. The arch measurements of each patient group were compared separately by the Wilcoxon rank sum (Mann-Whitney U) test, with a significance level of 5% (alpha = .05). Intraclass correlation measured the level of intraobserver agreement.Results: Patients with healthy teeth showed no significant difference between all DPM and CBCT arch measurements (P > .05). Patients with metallic restoration showed significant difference between DPM and CBCT for the majority of the arch measurements (P > .05). The two examiners showed excellent intraobserver agreement for both measuring methods with intraclass correlation coefficient higher than 0.95.Conclusion: CBCT provided the same accuracy as DPM in the measurement of the dental arches, and was negatively influenced by the presence of image artifacts.

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The idiopathic dilated cardiomyopathy (IDC) is one of the major public health problems in the western world. Patients with IDC in functional class IV (New York Health Association - NYHA), even after therapeutic optimization, have high mortality. Stem cell therapy has emerged as a potential therapeutic option for cell death-related heart diseases and several positive effects were assigned to cell therapy in cardiomyopathy. The aim of this study was identify short-term result of cell transplantation in idiopathic dilated cardiomyopathy patients (IDC) who were treated by transplantation of autologous bone marrow mononuclear cells (BMMC). Intracoronary injections of autologous BMMC were performed in eight patients with severe ventricle dysfunction (mean of left ventricle ejection fraction – LEVF=20.03%), cardiac mass muscle around 156.2 g and NYHA between III and IV grades, other 8 IDC patients received placebo. The IDCs were followed - up for one and two years, by magnetic resonance imaging (MRI). The results after one year showed significant improvement in LVEF (mean=181.4) and muscle mass increasing (mean=181.4 g), after two years the LVEF continued improving, reaching a mean of 32.69% and the cardiac muscle mass kept stable (mean=179.4 g). Excepted for one patient, all the other had improvement in the NYHA functional class. The placebo group did not show any improvement. We believe that BMMC implant may be a beneficial therapeutic option for IDC patients.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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In this letter, a semiautomatic method for road extraction in object space is proposed that combines a stereoscopic pair of low-resolution aerial images with a digital terrain model (DTM) structured as a triangulated irregular network (TIN). First, we formulate an objective function in the object space to allow the modeling of roads in 3-D. In this model, the TIN-based DTM allows the search for the optimal polyline to be restricted along a narrow band that is overlaid upon it. Finally, the optimal polyline for each road is obtained by optimizing the objective function using the dynamic programming optimization algorithm. A few seed points need to be supplied by an operator. To evaluate the performance of the proposed method, a set of experiments was designed using two stereoscopic pairs of low-resolution aerial images and a TIN-based DTM with an average resolution of 1 m. The experimental results showed that the proposed method worked properly, even when faced with anomalies along roads, such as obstructions caused by shadows and trees.

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Optical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. Since there is a lack of research that aims to automatically tune such parameters, in this work we have proposed an evolutionary-based framework for such task, thus introducing three techniques for such purpose: Particle Swarm Optimization, Harmony Search and Social-Spider Optimization. The proposed framework has been compared against with the well-known Large Displacement Optical Flow approach, obtaining the best results in three out eight image sequences provided by a public dataset. Additionally, the proposed framework can be used with any other optimization technique.

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The objective of the present study was to optimize a radiographic technique for hand examinations using a computed radiography (CR) system and demonstrate the potential for dose reductions compared with clinically established technique. An exposure index was generated from the optimized technique to guide operators when imaging hands. Homogeneous and anthropomorphic phantoms that simulated a patient's hand were imaged using a CR system at various tube voltages and current settings (40-55 kVp, 1.25-2.8 mAs), including those used in clinical routines (50 kVp, 2.0 mAs) to obtain an optimized chart. The homogeneous phantom was used to assess objective parameters that are associated with image quality, including the signal difference-to-noise ratio (SdNR), which is used to define a figure of merit (FOM) in the optimization process. The anthropomorphic phantom was used to subjectively evaluate image quality using Visual Grading Analysis (VGA) that was performed by three experienced radiologists. The technique that had the best VGA score and highest FOM was considered the gold standard (GS) in the present study. Image quality, dose and the exposure index that are currently used in the clinical routine for hand examinations in our institution were compared with the GS technique. The effective dose reduction was 67.0%. Good image quality was obtained for both techniques, although the exposure indices were 1.60 and 2.39 for the GS and clinical routine, respectively.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Electrical impedance tomography (EIT) is an imaging technique that attempts to reconstruct the impedance distribution inside an object from the impedance between electrodes placed on the object surface. The EIT reconstruction problem can be approached as a nonlinear nonconvex optimization problem in which one tries to maximize the matching between a simulated impedance problem and the observed data. This nonlinear optimization problem is often ill-posed, and not very suited to methods that evaluate derivatives of the objective function. It may be approached by simulated annealing (SA), but at a large computational cost due to the expensive evaluation process of the objective function, which involves a full simulation of the impedance problem at each iteration. A variation of SA is proposed in which the objective function is evaluated only partially, while ensuring boundaries on the behavior of the modified algorithm.

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In this work, a Monte Carlo code was used to investigate the performance of different x-ray spectra in digital mammography, through a figure of merit (FOM), defined as FOM = CNR2/(D) over bar (g), with CNR being the contrast-to-noise ratio in image and (D) over bar (g) being the average glandular dose. The FOM was studied for breasts with different thicknesses t (2 cm <= t <= 8 cm) and glandular contents (25%, 50% and 75% glandularity). The anode/filter combinations evaluated were those traditionally employed in mammography (Mo/Mo, Mo/Rh, Rh/Rh), and a W anode combined with Al or K-edge filters (Zr, Mo, Rh, Pd, Ag, Cd, Sn), for tube potentials between 22 and 34 kVp. Results show that the W anode combined with K-edge filters provides higher values of FOM for all breast thicknesses investigated. Nevertheless, the most suitable filter and tube potential depend on the breast thickness, and for t >= 6 cm, they also depend on breast glandularity. Particularly for thick and dense breasts, a W anode combined with K-edge filters can greatly improve the digital technique, with the values of FOM up to 200% greater than that obtained with the anode/filter combinations and tube potentials traditionally employed in mammography. For breasts with t < 4 cm, a general good performance was obtained with the W anode combined with 60 mu m of the Mo filter at 24-25 kVp, while 60 mu m of the Pd filter provided a general good performance at 24-26 kVp for t = 4 cm, and at 28-30 and 29-31 kVp for t = 6 and 8 cm, respectively.

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Network reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.

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[EN] We present an energy based approach to estimate a dense disparity map from a set of two weakly calibrated stereoscopic images while preserving its discontinuities resulting from image boundaries. We first derive a simplified expression for the disparity that allows us to estimate it from a stereo pair of images using an energy minimization approach. We assume that the epipolar geometry is known, and we include this information in the energy model. Discontinuities are preserved by means of a regularization term based on the Nagel-Enkelmann operator. We investigate the associated Euler-Lagrange equation of the energy functional, and we approach the solution of the underlying partial differential equation (PDE) using a gradient descent method The resulting parabolic problem has a unique solution. In order to reduce the risk to be trapped within some irrelevant local minima during the iterations, we use a focusing strategy based on a linear scalespace. Experimental results on both synthetic and real images arere presented to illustrate the capabilities of this PDE and scale-space based method.

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This Phd thesis was entirely developed at the Telescopio Nazionale Galileo (TNG, Roque de los Muchachos, La Palma Canary Islands) with the aim of designing, developing and implementing a new Graphical User Interface (GUI) for the Near Infrared Camera Spectrometer (NICS) installed on the Nasmyth A of the telescope. The idea of a new GUI for NICS has risen for optimizing the astronomers work through a set of powerful tools not present in the existing GUI, such as the possibility to move automatically, an object on the slit or do a very preliminary images analysis and spectra extraction. The new GUI also provides a wide and versatile image display, an automatic procedure to find out the astronomical objects and a facility for the automatic image crosstalk correction. In order to test the overall correct functioning of the new GUI for NICS, and providing some information on the atmospheric extinction at the TNG site, two telluric standard stars have been spectroscopically observed within some engineering time, namely Hip031303 and Hip031567. The used NICS set-up is as follows: Large Field (0.25'' /pixel) mode, 0.5'' slit and spectral dispersion through the AMICI prism (R~100), and the higher resolution (R~1000) JH and HK grisms.