Improving synthetic aperture image by image compounding in beamforming process

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.

A New and Simple Visual Technique Based on Indigo Dye for Determination of Ozone in Ambient Air

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Documentação oficial e o mito da educadora nata na educação infantil

O artigo descreve a trajetória, bem como apresenta as conclusões de pesquisa que resultou em dissertação de mestrado em educação, defendida em 1997, cujo objeto de estudo é o profissional que atua na educação infantil em nosso país. As análises levaram à conclusão de que, ao longo da história, tem-se reforçado a imagem do profissional dessa área como sendo a da mulher naturalmente educadora, passiva, paciente, amorosa, que sabe agir com bom senso, é guiada pelo coração, em detrimento da formação profissional. A não-valorização salarial, a inferioridade perante os demais docentes, a vinculação do seu trabalho com o doméstico e a deficiência articulam-se à difusão da figura mitificada, que não consegue desvincular-se das significações que interligam a mãe e a criança.

High Content Screening of a Kinase-Focused Library Reveals Compounds Broadly-Active against Dengue Viruses

Dengue virus is a mosquito-borne flavivirus that has a large impact in global health. It is considered as one of the medically important arboviruses, and developing a preventive or therapeutic solution remains a top priority in the medical and scientific community. Drug discovery programs for potential dengue antivirals have increased dramatically over the last decade, largely in part to the introduction of high-throughput assays. In this study, we have developed an image-based dengue high-throughput/high-content assay (HT/HCA) using an innovative computer vision approach to screen a kinase-focused library for anti-dengue compounds. Using this dengue HT/HCA, we identified a group of compounds with a 4-(1-aminoethyl)-N-methylthiazol-2-amine as a common core structure that inhibits dengue viral infection in a human liver-derived cell line (Huh-7.5 cells). Compounds CND1201, CND1203 and CND1243 exhibited strong antiviral activities against all four dengue serotypes. Plaque reduction and time-of-addition assays suggests that these compounds interfere with the late stage of viral infection cycle. These findings demonstrate that our image-based dengue HT/HCA is a reliable tool that can be used to screen various chemical libraries for potential dengue antiviral candidates. © 2013 Cruz et al.

FLEXLAB: Middleware de virtualização de hardware para gerenciamento centralizado de computadores em rede

Pós-graduação em Ciência da Computação - IBILCE

Identification of Novel Compounds Inhibiting Chikungunya Virus-Induced Cell Death by High Throughput Screening of a Kinase Inhibitor Library

Chikungunya virus (CHIKV) is a mosquito-borne arthrogenic alphavirus that causes acute febrile illness in humans accompanied by joint pains and in many cases, persistent arthralgia lasting weeks to years. The re-emergence of CHIKV has resulted in numerous outbreaks in the eastern hemisphere, and threatens to expand in the foreseeable future. Unfortunately, no effective treatment is currently available. The present study reports the use of resazurin in a cell-based high-throughput assay, and an image-based high-content assay to identify and characterize inhibitors of CHIKV-infection in vitro. CHIKV is a highly cytopathic virus that rapidly kills infected cells. Thus, cell viability of HuH-7 cells infected with CHIKV in the presence of compounds was determined by measuring metabolic reduction of resazurin to identify inhibitors of CHIKV-associated cell death. A kinase inhibitor library of 4,000 compounds was screened against CHIKV infection of HuH-7 cells using the resazurin reduction assay, and the cell toxicity was also measured in non-infected cells. Seventy-two compounds showing >= 50% inhibition property against CHIKV at 10 mu M were selected as primary hits. Four compounds having a benzofuran core scaffold (CND0335, CND0364, CND0366 and CND0415), one pyrrolopyridine (CND0545) and one thiazol-carboxamide (CND3514) inhibited CHIKV-associated cell death in a dose-dependent manner, with EC50 values between 2.2 mu M and 7.1 mu M. Based on image analysis, these 6 hit compounds did not inhibit CHIKV replication in the host cell. However, CHIKV-infected cells manifested less prominent apoptotic blebs typical of CHIKV cytopathic effect compared with the control infection. Moreover, treatment with these compounds reduced viral titers in the medium of CHIKV-infected cells by up to 100-fold. In conclusion, this cell-based high-throughput screening assay using resazurin, combined with the image-based high content assay approach identified compounds against CHIKV having a novel antiviral activity -inhibition of virus-induced CPE - likely by targeting kinases involved in apoptosis.

Development and applications of three-dimensional gamma ray tomography system using ray casting volume rendering techniques

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

Image registration and image interpolation in volume rendering of cross sections

We outline a method for registration of images of cross sections using the concepts of The Generalized Hough Transform (GHT). The approach may be useful in situations where automation should be a concern. To overcome known problems of noise of traditional GHT we have implemented a slight modified version of the basic algorithm. The modification consists of eliminating points of no interest in the process before the application of the accumulation step of the algorithm. This procedure minimizes the amount of accumulation points while reducing the probability of appearing of spurious peaks. Also, we apply image warping techniques to interpolate images among cross sections. This is needed where the distance of samples between sections is too large. Then it is suggested that the step of registration with GHT can help the interpolation automation by simplifying the correspondence between points of images. Some results are shown.

A method for the digital image analysis of ceramic grains based on shape factor segmentation

A very simple and robust method for ceramics grains quantitative image analysis is presented. Based on the use of optimal imaging conditions for reflective light microscopy of bulk samples, a digital image processing routine was developed for shading correction, noise suppressing and contours enhancement. Image analysis was done for grains selected according to their concavities, evaluated by perimeter ratio shape factor, to avoid consider the effects of breakouts and ghost boundaries due to ceramographic preparation limitations. As an example, the method was applied for two ceramics, to compare grain size and morphology distributions. In this case, most of artefacts introduced by ceramographic preparation could be discarded due to the use of perimeter ratio exclusion range.

JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

Is it possible to make pixel-based radar image classification user-friendly?

In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in order to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed. © 2011 IEEE.

Measurements of simulated periodontal bone defects in inverted digital image and film-based radiograph: An in vitro study

Purpose: This study was performed to compare the inverted digital images and film-based images of dry pig mandibles to measure the periodontal bone defect depth. Materials and Methods: Forty 2-wall bone defects were made in the proximal region of the premolar in the dry pig mandibles. The digital and conventional radiographs were taken using a Schick sensor and Kodak F-speed intraoral film. Image manipulation (inversion) was performed using Adobe Photoshop 7.0 software. Four trained examiners made all of the radiographic measurements in millimeters a total of three times from the cementoenamel junction to the most apical extension of the bone loss with both types of images: inverted digital and film. The measurements were also made in dry mandibles using a periodontal probe and digital caliper. The Student's t-test was used to compare the depth measurements obtained from the two types of images and direct visual measurement in the dry mandibles. A significance level of 0.05 for a 95% confidence interval was used for each comparison. Results: There was a significant difference between depth measurements in the inverted digital images and direct visual measurements (p>|t|=0.0039), with means of 6.29 mm (IC95%:6.04-6.54) and 6.79 mm (IC95%:6.45-7.11), respectively. There was a non-significant difference between the film-based radiographs and direct visual measurements (p>|t|=0.4950), with means of 6.64mm (IC95%:6.40-6.89) and 6.79mm(IC95%:6.45-7.11), respectively. Conclusion: The periodontal bone defect measurements in the inverted digital images were inferior to film-based radiographs, underestimating the amount of bone loss. copy; 2012 by Korean Academy of Oral and Maxillofacial Radiology.

A hybrid image restoration algorithm based on Projections onto Convex Sets and Harmony Search

Image restoration is a research field that attempts to recover a blurred and noisy image. Since it can be modeled as a linear system, we propose in this paper to use the meta-heuristics optimization algorithm Harmony Search (HS) to find out near-optimal solutions in a Projections Onto Convex Sets-based formulation to solve this problem. The experiments using HS and four of its variants have shown that we can obtain near-optimal and faster restored images than other evolutionary optimization approach. © 2013 IEEE.

OPF-MRF: Optimum-path forest and Markov random fields for contextual-based image classification

Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, we propose an approach which unifies a supervised learning algorithm - namely Optimum-Path Forest - together with a Markov Random Field in order to build a prior model holding a spatial smoothness assumption, which takes into account the contextual information for classification purposes. We show its robustness for brain tissue classification over some images of the well-known dataset IBSR. © 2013 Springer-Verlag.

A scalable re-ranking method for content-based image retrieval

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