45 resultados para Multilevel thresholding
em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"
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This paper presents a method for the quantification of cellular rejection in endomyocardial biopsies of patients submitted to heart transplant. The model is based on automatic multilevel thresholding, which employs histogram quantification techniques, histogram slope percentage analysis and the calculation of maximum entropy. The structures were quantified with the aid of the multi-scale fractal dimension and lacunarity for the identification of behavior patterns in myocardial cellular rejection in order to determine the most adequate treatment for each case.
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The digital image processing has been applied in several areas, especially where it is necessary use tools for feature extraction and to get patterns of the studied images. In an initial stage, the segmentation is used to separate the image in parts that represents a interest object, that may be used in a specific study. There are several methods that intends to perform such task, but is difficult to find a method that can easily adapt to different type of images, that often are very complex or specific. To resolve this problem, this project aims to presents a adaptable segmentation method, that can be applied to different type of images, providing an better segmentation. The proposed method is based in a model of automatic multilevel thresholding and considers techniques of group histogram quantization, analysis of the histogram slope percentage and calculation of maximum entropy to define the threshold. The technique was applied to segment the cell core and potential rejection of tissue in myocardial images of biopsies from cardiac transplant. The results are significant in comparison with those provided by one of the best known segmentation methods available in the literature. © 2010 IEEE.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The aim of the present study was to investigate the presence of contaminants in the mussel Perna perna from Sao Sebastiao Channel, São Paulo, Brazil, and to evaluate the effects of these contaminants on these organisms at biochemical (catalase [CAT], glutathione-S-transferase [GST], and cholinesterase [ChE]), cellular (neutral red retention time [NRRT] assay), and physiological (cardiac monitoring) levels. Two sampling surveys were performed (winter of 2001 and summer of 2002) at six stations along the channel: Cigarras, station 1; late Clube de Ilhabela, station 2; Oil Terminal, station 3; Toque Toque, station 4; Ponta da Sela, station 5 (reference station); and Taubate, station 6. Differences in CAT activity were observed between mussels from stations 3 and 5 during the winter, but no differences were detected in the summer. No differences in GST activity were found among stations during the winter, although animals from station 3 showed higher activity during the summer. The ChE activity was significantly higher in the mussels from stations I and 2 during the winter and from stations I and 3 during the summer. Organisms from stations I through 4 showed statistically lower NRRT in both seasons. Similar heart rates were observed in the mussels from all stations. Hydrocarbons were detected in organisms from all the stations in both seasons. During the winter, higher polycyclic aromatic hydrocarbon (PAH) levels were observed in organisms from station 3, whereas during the summer, higher levels of metals were found in organisms from stations 1, 3, and 4. The multivariate analyses showed a strong influence of PAHs on the winter biological results, but metals showed higher influence on these responses in the summer, indicating multiple contaminant sources.
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This paper presents the comparison of three topologies of multilevel inverters applied to drive an induction motor of 500 kVA/4.16 kV. The multilevel inverters analyzed are: a neutral point clamped inverter, a symmetrical cascaded multilevel inverter and a hybrid asymmetrical cascaded multilevel inverter. The performance indexes used in the comparison are total harmonic distortion, first order distortion factor, semiconductors power losses distribution and heat-sink volume. The comparison is developed with the purpose of finding the efficiency and the heat-sink volume where the three systems present the same output filter. ©2008 IEEE.
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High blood pressure (HBP) and obesity is a well-established major risk factor for stroke and coronary heart disease. However, the literatures are scarce about these informations in adolescents from low-and-middle income countries. This school-based survey was carried out among students from Maringá (Brazil) and Buenos Aires (Argentina) selected random sampling. We studied 991 Brazilian adolescents (54.5% girls) in the age range of 14-18 years. In Argentina, we studied 933 adolescents (45.9% female) in the age range of 11-17 years. The outcomes of this study are general obesity, abdominal obesity and HBP. The associated factors analysed were gender, age and health behaviours. The prevalence of obesity was 5.8% in Brazil and 2.8% in Argentina, the prevalence of abdominal obesity was 32.7% in Brazil and 11.1% in Argentina, the prevalence of HBP was 14.9% in Brazil and 13.5% in Argentina. The multilevel analysis showed that older adolescents (>14 years old) have a little likelihood of being overweight, whereas male adolescents are more likely to be obese and have HBP. The abdominal obesity in both indicators were not associated with the independent variables. The prevalence of cardiovascular risk factors is high in Latin American adolescents independent of each country, and was associated with male gender.Journal of Human Hypertension advance online publication, 15 August 2013; doi:10.1038/jhh.2013.74.
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The wavelet transform is used to reduce the high frequency multipath of pseudorange and carrier phase GPS double differences (DDs). This transform decomposes the DD signal, thus separating the high frequencies due to multipath effects. After the decomposition, the wavelet shrinkage is performed by thresholding to eliminate the high frequency component. Then the signal can be reconstructed without the high frequency component. We show how to choose the best threshold. Although the high frequency multipath is not the main multipath error component, its correction provides improvements of about 30% in pseudorange average residuals and 24% in carrier phases. The results also show that the ambiguity solutions become more reliable after correcting the high frequency multipath.
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In this paper a methodology for automatic extraction of road segments from images with different resolutions (low, middle and high resolution) is presented. It is based on a generalized concept of lines in digital images, by which lines can be described by the centerlines of two parallel edges. In the specific case of low resolution images, where roads are manifested as entities of 1 or 2 pixels wide, the proposed methodology combines an automatic image enhancement operation with the following strategies: automatic selection of the hysteresis thresholds and the Gaussian scale factor; line length thresholding; and polygonization. In medium and high resolution images roads manifest as narrow and elongated ribbons and, consequently, the extraction goal becomes the road centerlines. In this case, it is not necessary to apply the previous enhancement step used to enhance roads in low resolution images. The results obtained in the experimental evaluation satisfied all criteria established for the efficient extraction of road segments from different resolution images, providing satisfactory results in a completely automatic way.
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In this paper is a totally automatic strategy proposed to reduce the complexity of patterns ( vegetation, building, soils etc.) that interact with the object 'road' in color images, thus reducing the difficulty of the automatic extraction of this object. The proposed methodology consists of three sequential steps. In the first step the punctual operator is applied for artificiality index computation known as NandA ( Natural and Artificial). The result is an image whose the intensity attribute is the NandA response. The second step consists in automatically thresholding the image obtained in the previous step, resulting in a binary image. This image usually allows the separation between artificial and natural objects. The third step consists in applying a preexisting road seed extraction methodology to the previous generated binary image. Several experiments carried out with real images made the verification of the potential of the proposed methodology possible. The comparison of the obtained result to others obtained by a similar methodology for road seed extraction from gray level images, showed that the main benefit was the drastic reduction of the computational effort.
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Computer systems are used to support breast cancer diagnosis, with decisions taken from measurements carried out in regions of interest (ROIs). We show that support decisions obtained from square or rectangular ROIs can to include background regions with different behavior of healthy or diseased tissues. In this study, the background regions were identified as Partial Pixels (PP), obtained with a multilevel method of segmentation based on maximum entropy. The behaviors of healthy, diseased and partial tissues were quantified by fractal dimension and multiscale lacunarity, calculated through signatures of textures. The separability of groups was achieved using a polynomial classifier. The polynomials have powerful approximation properties as classifiers to treat characteristics linearly separable or not. This proposed method allowed quantifying the ROIs investigated and demonstrated that different behaviors are obtained, with distinctions of 90% for images obtained in the Cranio-caudal (CC) and Mediolateral Oblique (MLO) views.
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Wavelets are being extensively used in Geodetic applications. In this paper, the Multi-Resolution Analysis (MRA) using wavelets is applied to pseudorange and carrier phase GPS double differences (DDs) in order to reduce multipath effects. The wavelets were already applied to GPS carrier phase DDs, but some questions remain: How good can be the results, and are all multipath effects reduced? The answers to these questions are discussed in this paper. Thus, the wavelet transform is used to decompose the DD signals, splitting them in lower resolution components. After the decomposition process, the wavelet shrinkage is performed by thresholding to eliminate the components relative to multipath effects. Then, the DD observation can be reconstructed. This new DD signal is used to perform the baseline processing. The daily multipath repeatability was verified. With the application of the proposed approach, the results showed that the reliability of the ambiguity resolution and accuracy of the results improved when compared with the standard procedure. Furthermore, the method showed to be very efficient computationally, because, it is not noticed, at practical level, difference in the time span between the processing with and without application of the proposed method. However, only the high frequency multipath was eliminated.
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In this work a new method is proposed for noise reduction in speech signals in the wavelet domain. The method for signal processing makes use of a transfer function, obtained as a polynomial combination of three processings, denominated operators. The proposed method has the objective of overcoming the deficiencies of the thresholding methods and the effective processing of speech corrupted by real noises. Using the method, two speech signals are processed, contaminated by white noise and colored noises. To verify the quality of the processed signals, two evaluation measures are used: signal to noise ratio (SNR) and perceptual evaluation of speech quality (PESQ).
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This paper aims at extracting street centerlines from previously isolated street regions by using the image of laser scanning intensity. In this image, streets are easily identified, since they manifest as dark, elongate ribbons contrasting with background objects. The intensity image is segmented by using the region growing technique, which generates regions representing the streets. From these regions, the street centerlines are extracted in two manners. The first one is through the Steger lines detection method combined with a line length thresholding by which lines being shorter than a minimum length are removed. The other manner is by combining the skeletonization method of regions based on the Medial Axis Transform and with a pruning process to eliminate as much as possible the ramifications. Experiments showed that the Steger-based method provided results better than the method based on skeletonization.
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The posterior position in the arches is one of the factors that underlies the poor prognosis of molar teeth (M). It is speculated that M do not benefit from the oral hygiene routine as well as non-molars (NM) do. This study evaluated the response of M and NM to supragingival control during a 6-month period in 25 smokers (S) and 25 never-smokers (NS) with moderate-to-severe periodontitis. One calibrated examiner assessed visible plaque (VPI) and gingival bleeding (GBI) indexes, periodontal probing depth (PPD), bleeding on probing (BOP), and clinical attachment loss (CAL) at days 0 (baseline), 30 and 180. At baseline, M showed significantly higher mean values of VPI (p = 0.017) and PPD (p < 0.001) compared with NM; CAL was also greater in M (p < 0.001) and was affected by smoking (p = 0.007). The reductions obtained for periodontal indicators at day 180 showed similar responses between M and NM. For CAL, M (NS 0.57 ± 0.50; S 0.67 ± 0.64) and NM (NS 0.38 ± 0.23; S 0.50 ± 0.33) reached an almost significant difference (p = 0.05). Smoking did not influence the response to treatment. Multilevel analysis revealed that, only for PDD reductions, the interaction between sites, teeth and patient was significant (p < 0.001). It was concluded that M benefit from an adequate regimen of supragingival biofilm control; therefore, supragingival condition should be considered in the prognosis of molar teeth.
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Objectives: To examine the independent and combined association of physical activity (PA) and sedentary behavior (SB) on both systolic (SBP) and diastolic blood pressure (DBP) in adolescents from two observational studies. Methods: Participants from two cross-sectional studies, one conducted in Europe (n = 3,308; HELENA study) and the other in Brazil (n = 991; BRACAH study), were selected by complex sampling. Systolic and diastolic blood pressure (outcomes), PA and SB, both independently and combined, and potential confounders were analyzed. Associations were examined by multilevel linear regression. Results: Performing the recommended amount of PA (≥60 min/d) attenuated the effect of SB on DBP in BRACAH study girls and in boys from both studies. In contrast, PA did not attenuate the effects of SB on the SBP of girls in the HELENA study. The combination of less than recommended levels of PA with 2-4 h/d of sedentary behavior was found to be associated with increased SBP in boys from both studies. Conclusions: Meeting current PA recommendations could mediate the association between SB and DBP in both sexes. In boys, the joint effect of low levels of PA and excessive sedentary activity increases SBP levels. Longitudinal studies are required to confirm these findings. © 2013 de Moraes et al.