907 resultados para Evaluation methods for image segmentation


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Intestinal parasitosis constitutes a serious health problem in most tropical countries. The diagnosis of enteroparasites in laboratory routine relies on the examination of stool samples using optical microscopy and the error rates usually range from moderate to high. Approaches based on automatic image analysis have been proposed, but the methods are usually specific for some species, some of them are computationally expensive, and image acquisition and focus are manual. We present a solution to automate the diagnosis of the 15 most common species of enteroparasites in Brazil, using a sensitive parasitological technique, a motorized microscope with digital camera for automatic image acquisition and focus, and fast image analysis methods. The results indicate that our solution is effective and suitable for laboratory routine, in which the exam must be concluded in a few minutes. © 2013 IEEE.

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Demand response has gained increasing importance in the context of competitive electricity markets and smart grid environments. In addition to the importance that has been given to the development of business models for integrating demand response, several methods have been developed to evaluate the consumers' performance after the participation in a demand response event. The present paper uses those performance evaluation methods, namely customer baseline load calculation methods, to determine the expected consumption in each period of the consumer historic data. In the cases in which there is a certain difference between the actual consumption and the estimated consumption, the consumer is identified as a potential cause of non-technical losses. A case study demonstrates the application of the proposed method to real consumption data. © 2013 IEEE.

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PURPOSE: To investigate and compare the biocompatibility of two types of Ferrara intracorneal ring segment: with and without chondroitin sulfate coating by clinical and histopathological evaluation. METHODS: A randomized experimental study was carried out on thirty right-eye corneas from 30 Norfolk albino rabbits allocated into two experimental groups: Group G1 - implanted with Ferrara intracorneal ring segment without coating (FICRS) and Group G2 - implanted with Ferrara intracorneal ring segment with chondroitin sulfate coating (FICRS-CS). Left eyes formed the control group. Clinical parameters analyzed were: presence of edema, vascularization, infection and ring extrusion one, 30, and 60 days after surgery. Histopathological parameters analyzed were: number of corneal epithelial layers over and adjacent to the ring, presence of spongiosis, hydropic degeneration, basement membrane thinning, inflammatory cells, neovascularization and pseudocapsule formation. RESULTS: At clinical examination 60 days after implant, edema, vascularization and extrusion were observed respectively in 20%, 26.7%, 6.7% of FICRS corneas and in 6.7%, 6.7%, and 0% of FICRS-CS corneas. Histopathological evaluation showed epithelial-layer reduction from 5 (5;6) to 3 (3;3) with FICRS and from 5 (5;5) to 4 (3;5) with FICRS-CS in the region over the ring. Epithelial spongiosis, hydropic degeneration, and basement membrane thinning were present in 69.2%, 53.8%, and 69.2% of FICRS and in 73.3%, 73.3%, and 46.7% with FICRS-CS, respectively. Vascularization was present in 38.5% of FICRS and 13.3% with FICRS-CS, inflammatory cells in 75% of FICRS and 33.3% with FICRS-CS, and pseudocapsule in 66.7% of FICRS and 93.3% with FICRS-CS. Giant cells occurred only in the FICRS-CS group (20%). CONCLUSION: Ferrara intracorneal rings coated with chondroitin sulfate (FICRS-CS) caused lower frequency of clinical and histopathological alterations than Ferrara intracorneal rings without the coating (FICRS), demonstrating higher biocompatibility of the FICRS-CS.

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Human intestinal parasites constitute a problem in most tropical countries, causing death or physical and mental disorders. Their diagnosis usually relies on the visual analysis of microscopy images, with error rates that may range from moderate to high. The problem has been addressed via computational image analysis, but only for a few species and images free of fecal impurities. In routine, fecal impurities are a real challenge for automatic image analysis. We have circumvented this problem by a method that can segment and classify, from bright field microscopy images with fecal impurities, the 15 most common species of protozoan cysts, helminth eggs, and larvae in Brazil. Our approach exploits ellipse matching and image foresting transform for image segmentation, multiple object descriptors and their optimum combination by genetic programming for object representation, and the optimum-path forest classifier for object recognition. The results indicate that our method is a promising approach toward the fully automation of the enteroparasitosis diagnosis. © 2012 IEEE.

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Apresenta-se nesta dissertação a proposta de um algoritmo supervisionado de classificação de imagens de sensoreamento remoto, composto de três etapas: remoção ou suavização de nuvens, segmentação e classificação.O método de remoção de nuvens usa filtragem homomórfica para tratar as obstruções causadas pela presença de nuvens suaves e o método Inpainting para remover ou suavizar a preseça de sombras e nuvens densas. Para as etapas de segmentação e classificação é proposto um método baseado na energia AC dos coeficientes da Transformada Cosseno Discreta (DCT). O modo de classificação adotado é do tipo supervisionado. Para avaliar o algioritmo foi usado um banco de 14 imagens captadas por vários sensores, das quais 12 possuem algum tipo de obstrução. Para avaliar a etapa de remoção ou suavização de nuvens e sombras são usados a razão sinal-ruído de pico (PSNR) e o coeficiente Kappa. Nessa fase, vários filtros passa-altas foram comparados para a escolha do mais eficiente. A segmentação das imagens é avaliada pelo método da coincidência entre bordas (EBC) e a classificação é avaliada pela medida da entropia relativa e do erro médio quadrático (MSE). Tão importante quanto as métricas, as imagens resultantes são apresentadas de forma a permitir a avaliação subjetiva por comparação visual. Os resultados mostram a eficiência do algoritmo proposto, principalmente quando comparado ao software Spring, distribuído pelo Instituto Nacional de Pesquisas Espaciais (INPE).

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Introduction Literature data are not conclusive as to the influence of neonatal complications in the maturational process of the auditory system observed by auditory brainstem response (ABR) in infants at term and preterm. Objectives Check the real influence of the neonatal complications in infants by the sequential auditory evaluation. Methods Historical cohort study in a tertiary referral center. A total of 114 neonates met inclusion criteria: treatment at the Universal Neonatal Hearing Screening Program of the local hospital; at least one risk indicator for hearing loss; presence in both evaluations (the first one after hospital discharge from the neonatal unit and the second one at 6 months old); all latencies in ABR and transient otoacoustic emissions present in both ears. Results The complications that most influenced the ABR findings were Apgar scores less than 6 at 5 minutes, gestational age, intensive care unit stay, peri-intraventricular hemorrhage, and mechanical ventilation. Conclusion Sequential auditory evaluation is necessary in premature and term newborns with risk indicators for hearing loss to correctly identify injuries in the auditory pathway.

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Pós-graduação em Ciência da Computação - IBILCE

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Color texture classification is an important step in image segmentation and recognition. The color information is especially important in textures of natural scenes, such as leaves surfaces, terrains models, etc. In this paper, we propose a novel approach based on the fractal dimension for color texture analysis. The proposed approach investigates the complexity in R, G and B color channels to characterize a texture sample. We also propose to study all channels in combination, taking into consideration the correlations between them. Both these approaches use the volumetric version of the Bouligand-Minkowski Fractal Dimension method. The results show a advantage of the proposed method over other color texture analysis methods. (C) 2011 Elsevier Ltd. All rights reserved.

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In this paper we address the "skull-stripping" problem in 3D MR images. We propose a new method that employs an efficient and unique histogram analysis. A fundamental component of this analysis is an algorithm for partitioning a histogram based on the position of the maximum deviation from a Gaussian fit. In our experiments we use a comprehensive image database, including both synthetic and real MRI. and compare our method with other two well-known methods, namely BSE and BET. For all datasets we achieved superior results. Our method is also highly independent of parameter tuning and very robust across considerable variations of noise ratio.

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Background: In the Global postural re-education (GPR) evaluation, posture alterations are associated with anterior or posterior muscular chain impairments. Our goal was to assess the reliability of the GPR muscular chain evaluation. Methods: Design: Inter-rater reliability study. Fifty physical therapists (PTs) and two experts trained in GPR assessed the standing posture from photographs of five youths with idiopathic scoliosis using a posture analysis grid with 23 posture indices (PI). The PTs and experts indicated the muscular chain associated with posture alterations. The PTs were also divided into three groups according to their experience in GPR. Experts' results (after consensus) were used to verify agreement between PTs and experts for muscular chain and posture assessments. We used Kappa coefficients (K) and the percentage of agreement (%A) to assess inter-rater reliability and intra-class coefficients (ICC) for determining agreement between PTs and experts. Results: For the muscular chain evaluation, reliability was moderate to substantial for 12 PI for the PTs (% A: 56 to 82; K: 0.42 to 0.76) and perfect for 19 PI for the experts. For posture assessment, reliability was moderate to substantial for 12 PI for the PTs (% A > 60%; K: 0.42 to 0.75) and moderate to perfect for 18 PI for the experts (% A: 80 to 100; K: 0.55 to 1.00). The agreement between PTs and experts was good for most muscular chain evaluations (18 PI; ICC: 0.82 to 0.99) and PI (19 PI; ICC: 0.78 to 1.00). Conclusions: The GPR muscular chain evaluation has good reliability for most posture indices. GPR evaluation should help guide physical therapists in targeting affected muscles for treatment of abnormal posture patterns.

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Objective To evaluate the effectiveness of two screening methods (imitanciometry screening and questionnaire) to identify children at risk for conductive hearing loss, comparing this data with complete audiologic evaluation. Methods Of 507 children aged between three and six, 111 completed all procedures. The observational methods used were: imitanciometry screening, a questionnaire to identify risk factors for hearing loss and complete audiologic evaluation. Results obtained in the first two instruments were compared with results from complete audiologic evaluation (gold standard). From these comparisons, sensitivity and specificity, accuracy, positive and negative predictive values, and odds ratio were determined for the two screening methods and for the combination of both methods. Results The two methods applied in series (questionnaire and after imitanciometry screening) showed a greater odds ratio and better correlation between sensitivity and proportion of false-positives (ROC curve). Conclusion Combining the two tests in series improved screening accuracy. This combination was the best tool for identifying children at risk for conductive hearing loss.

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[EN] OBJECTIVE: Our hypothesis is that sonography performed by the rheumatologist in patients with suspected carpal tunnel syndrome (CTS) has higher diagnostic value compared to physical evaluation. METHODS: Adult patients with suspected idiopathic CTS, defined by sensory symptoms over the distribution of the median nerve with or without positive results with the Phalen and/or the Tinel's maneuvers were included. The diagnosis of CTS was indicated by typical symptoms daily for at least 3 months and a positive nerve conduction study. One rheumatologist unaware of the clinical and electrodiagnostic results performed an ultrasound examination of the median nerve for the area ranging from the inlet to the outlet of the carpal tunnel. Mean cross-sectional area at each level, flattening ratio and bowing of flexor retinaculum were obtained. RESULTS: Sixty-eight patients with 105 affected wrists were examined. Tinel's and Phalen's signs had a closer sensitivity (73% and 67% respectively) and specificity (40% and 30% respectively). The best swelling nerve cut-off by sonography was 9.7 mm2 at the tunnel inlet, with a sensitivity of 86%, a specificity of 48% and accuracy of 77%. A 100% positive predictive value was reached with a cross-sectional area of 13 mm2, involving 33 hands (31% of the whole sample). Maximal cross sectional area and the measurement of flexor retinaculum had an accuracy of 72% and 73% respectively. Combination of physical maneuvers and sonography not yielded more accuracy than cross-sectional area itself. CONCLUSION: In patients with clinical history of idiopathic CTS and positive nerve conduction study, sonography performed by the rheumatologist has higher diagnostic value than physical maneuvers.

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In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.

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Extraction of both pelvic and femoral surface models of a hip joint from CT data for computer-assisted pre-operative planning of hip arthroscopy is addressed. We present a method for a fully automatic image segmentation of a hip joint. Our method works by combining fast random forest (RF) regression based landmark detection, atlas-based segmentation, with articulated statistical shape model (aSSM) based hip joint reconstruction. The two fundamental contributions of our method are: (1) An improved fast Gaussian transform (IFGT) is used within the RF regression framework for a fast and accurate landmark detection, which then allows for a fully automatic initialization of the atlas-based segmentation; and (2) aSSM based fitting is used to preserve hip joint structure and to avoid penetration between the pelvic and femoral models. Validation on 30 hip CT images show that our method achieves high performance in segmenting pelvis, left proximal femur, and right proximal femur surfaces with an average accuracy of 0.59 mm, 0.62 mm, and 0.58 mm, respectively.