685 resultados para Image Compounding
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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In this work, signal processing techniques are used to improve the quality of image based on multi-element synthetic aperture techniques. Using several apodization functions to obtain different side lobes distribution, a polarity function and a threshold criterium are used to develop an image compounding technique. The spatial diversity is increased using an additional array, which generates complementary information about the defects, improving the results of the proposed algorithm and producing high resolution and contrast images. The inspection of isotropic plate-like structures using linear arrays and Lamb waves is presented. Experimental results are shown for a 1-mm-thick isotropic aluminum plate with artificial defects using linear arrays formed by 30 piezoelectric elements, with the low dispersion symmetric mode S0 at the frequency of 330 kHz. © 2011 American Institute of Physics.
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Piezoelectric array transducers applications are becoming usual in the ultrasonic non-destructive testing area. However, the number of elements can increase the system complexity, due to the necessity of multichannel circuitry and to the large amount of data to be processed. Synthetic aperture techniques, where one or few transmission and reception channels are necessary, and the data are post-processed, can be used to reduce the system complexity. Another possibility is to use sparse arrays instead of a full-populated array. In sparse arrays, there is a smaller number of elements and the interelement spacing is larger than half wavelength. In this work, results of ultrasonic inspection of an aluminum plate with artificial defects using guided acoustic waves and sparse arrays are presented. Synthetic aperture techniques are used to obtain a set of images that are then processed with an image compounding technique, which was previously evaluated only with full-populated arrays, in order to increase the resolution and contrast of the images. The results with sparse arrays are equivalent to the ones obtained with full-populated arrays in terms of resolution. Although there is an 8 dB contrast reduction when using sparse arrays, defect detection is preserved and there is the advantage of a reduction in the number of transducer elements and data volume. © 2013 Brazilian Society for Automatics - SBA.
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This paper describes an image compounding technique based on the use of different apodization functions, the evaluation of the signals phases and information from the interaction of different propagation modes of Lamb waves with defects for enhanced damage detection, resolution and contrast. A 16 elements linear array is attached to a 1 mm thickness isotropic aluminum plate with artificial defects. The array can excite the fundamental A0 and S0 modes at the frequencies of 100 kHz and 360 kHz, respectively. For each mode two synthetic aperture (SA) images with uniform and Blackman apodization and one image of Coherence Factor Map (CFM) are obtained. The specific interaction between each propagation mode and the defects and the characteristics of acoustic radiation patterns due to different apodization functions result in images with different resolution and contrast. From the phase information one of the SA images is selected at each pixel to compound the final image. The SA images are multiplied by the CFM image to improve contrast and for the dispersive A0 mode it is used a technique for dispersion compensation. There is a contrast improvement of 47.5 dB, reducing the dead zone and improving resolution and damage detection. © 2012 IEEE.
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Several Lamb wave modes can be coupled to a particular structure, depending on its geometry and transducer used to generate the guided waves. Each Lamb mode interacts in a particular form with different types of defects, like notches, delamination, surface defects, resulting in different information which can be used to improve damage detection and characterization. An image compounding technique that uses the information obtained from different propagation modes of Lamb waves for non-destructive testing of plate-like structures is proposed. A linear array consisting of 16 piezoelectric elements is attached to a 1 mm thickness aluminum plate, coupling the fundamental A0 and S0 modes at the frequencies of 100 kHz and 360 kHz, respectively. For each mode two images are obtained from amplitude and phase information: one image using the Total Focusing Method (TFM) and one phase image obtained from the Sign Coherence Factor (SCF). Each TFM image is multiplied by the SCF image of the respective mode to improve contrast and reduce side and grating lobes effects. The high dispersive characteristic of the A0 mode is compensated for adequate defect detection. The information in the SCF images is used to select one of the TFM mode images, at each pixel, to obtain the compounded image. As a result, dead zone is reduced, resolution and contrast are improved, enhancing damage detection when compared to the use of only one mode. © 2013 Elsevier Ltd.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Several Lamb wave modes can be coupled to a particular structure, depending on its geometry and transducer used to generate the guided waves. Each Lamb mode interacts in a particular form with different types of defects, like notches, delamination, surface defects, resulting in different information which can be used to improve damage detection and characterization. An image compounding technique that uses the information obtained from different propagation modes of Lamb waves for non-destructive testing of plate-like structures is proposed. A linear array consisting of 16 piezoelectric elements is attached to a 1 mm thickness aluminum plate, coupling the fundamental A0 and SO modes at the frequencies of 100 kHz and 360 kHz, respectively. For each mode two images are obtained from amplitude and phase information: one image using the Total Focusing Method (TFM) and one phase image obtained from the Sign Coherence Factor (SCF). Each TFM image is multiplied by the SCF image of the respective mode to improve contrast and reduce side and grating lobes effects. The high dispersive characteristic of the A0 mode is compensated for adequate defect detection. The information in the SCF images is used to select one of the TFM mode images, at each pixel, to obtain the compounded image. As a result, dead zone is reduced, resolution and contrast are improved, enhancing damage detection when compared to the use of only one mode. (C) 2013 Elsevier Ltd. All rights reserved. (AU)
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This work describes preliminary results of a two-modality imaging system aimed at the early detection of breast cancer. The first technique is based on compounding conventional echographic images taken at regular angular intervals around the imaged breast. The other modality obtains tomographic images of propagation velocity using the same circular geometry. For this study, a low-cost prototype has been built. It is based on a pair of opposed 128-element, 3.2 MHz array transducers that are mechanically moved around tissue mimicking phantoms. Compounded images around 360 degrees provide improved resolution, clutter reduction, artifact suppression and reinforce the visualization of internal structures. However, refraction at the skin interface must be corrected for an accurate image compounding process. This is achieved by estimation of the interface geometry followed by computing the internal ray paths. On the other hand, sound velocity tomographic images from time of flight projections have been also obtained. Two reconstruction methods, Filtered Back Projection (FBP) and 2D Ordered Subset Expectation Maximization (2D OSEM), were used as a first attempt towards tomographic reconstruction. These methods yield useable images in short computational times that can be considered as initial estimates in subsequent more complex methods of ultrasound image reconstruction. These images may be effective to differentiate malignant and benign masses and are very promising for breast cancer screening. (C) 2015 The Authors. Published by Elsevier B.V.
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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PURPOSE: Juvenile idiopathic arthritis (JIA) has unknown etiology, and the involvement of the temporomandibular joint (TMJ) is rare in the early phase of the disease. The present article describes the use of computed tomography (CT) and magnetic resonance (MRI) images for the diagnosis of affected TMJ in JIA. CASE DESCRIPTION: A 12-year-old, female, Caucasian patient, with systemic rheumathoid arthritis and involvement of multiple joints was referred to the Imaging Center for TMJ assessment. The patient reported TMJ pain and limited opening of the mouth. The helical CT examination of the TMJ region showed asymmetric mandibular condyles, erosion of the right condyle and osteophyte-like formation. The MRI examination showed erosion of the right mandibular condyle, osteophytes, displacement without reduction and disruption of the articular disc. CONCLUSION: The disorders of the TMJ as a consequence of JIA must be carefully assessed by modern imaging methods such as CT and MRI. CT is very useful for the evaluation of discrete bone changes, which are not identified by conventional radiographs in the early phase of JIA. MRI allows the evaluation of soft tissues, the identification of acute articular inflammation and the differentiation between pannus and synovial hypertrophy.
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Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.
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Background: The present work aims at the application of the decision theory to radiological image quality control ( QC) in diagnostic routine. The main problem addressed in the framework of decision theory is to accept or reject a film lot of a radiology service. The probability of each decision of a determined set of variables was obtained from the selected films. Methods: Based on a radiology service routine a decision probability function was determined for each considered group of combination characteristics. These characteristics were related to the film quality control. These parameters were also framed in a set of 8 possibilities, resulting in 256 possible decision rules. In order to determine a general utility application function to access the decision risk, we have used a simple unique parameter called r. The payoffs chosen were: diagnostic's result (correct/incorrect), cost (high/low), and patient satisfaction (yes/no) resulting in eight possible combinations. Results: Depending on the value of r, more or less risk will occur related to the decision-making. The utility function was evaluated in order to determine the probability of a decision. The decision was made with patients or administrators' opinions from a radiology service center. Conclusion: The model is a formal quantitative approach to make a decision related to the medical imaging quality, providing an instrument to discriminate what is really necessary to accept or reject a film or a film lot. The method presented herein can help to access the risk level of an incorrect radiological diagnosis decision.
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Background: Chrysotile is considered less harmful to human health than other types of asbestos fibers. Its clearance from the lung is faster and, in comparison to amphibole forms of asbestos, chrysotile asbestos fail to accumulate in the lung tissue due to a mechanism involving fibers fragmentation in short pieces. Short exposure to chrysotile has not been associated with any histopathological alteration of lung tissue. Methods: The present work focuses on the association of small chrysotile fibers with interphasic and mitotic human lung cancer cells in culture, using for analyses confocal laser scanning microscopy and 3D reconstructions. The main goal was to perform the analysis of abnormalities in mitosis of fibers-containing cells as well as to quantify nuclear DNA content of treated cells during their recovery in fiber-free culture medium. Results: HK2 cells treated with chrysotile for 48 h and recovered in additional periods of 24, 48 and 72 h in normal medium showed increased frequency of multinucleated and apoptotic cells. DNA ploidy of the cells submitted to the same chrysotile treatment schedules showed enhanced aneuploidy values. The results were consistent with the high frequency of multipolar spindles observed and with the presence of fibers in the intercellular bridge during cytokinesis. Conclusion: The present data show that 48 h chrysotile exposure can cause centrosome amplification, apoptosis and aneuploid cell formation even when long periods of recovery were provided. Internalized fibers seem to interact with the chromatin during mitosis, and they could also interfere in cytokinesis, leading to cytokinesis failure which forms aneuploid or multinucleated cells with centrosome amplification.
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Multispectral widefield optical imaging has the potential to improve early detection of oral cancer. The appropriate selection of illumination and collection conditions is required to maximize diagnostic ability. The goals of this study were to (i) evaluate image contrast between oral cancer/precancer and non-neoplastic mucosa for a variety of imaging modalities and illumination/collection conditions, and (ii) use classification algorithms to evaluate and compare the diagnostic utility of these modalities to discriminate cancers and precancers from normal tissue. Narrowband reflectance, autofluorescence, and polarized reflectance images were obtained from 61 patients and 11 normal volunteers. Image contrast was compared to identify modalities and conditions yielding greatest contrast. Image features were extracted and used to train and evaluate classification algorithms to discriminate tissue as non-neoplastic, dysplastic, or cancer; results were compared to histologic diagnosis. Autofluorescence imaging at 405-nm excitation provided the greatest image contrast, and the ratio of red-to-green fluorescence intensity computed from these images provided the best classification of dysplasia/cancer versus non-neoplastic tissue. A sensitivity of 100% and a specificity of 85% were achieved in the validation set. Multispectral widefield images can accurately distinguish neoplastic and non-neoplastic tissue; however, the ability to separate precancerous lesions from cancers with this technique was limited. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3516593]