Anodic porous alumina structural characteristics study based on SEM image processing and analysis

The present work reports the porous alumina structures fabrication and their quantitative structural characteristics study based on mathematical morphology analysis by using the SEM images. The algorithm used in this work was implemented in 6.2 MATLAB software. Using the algorithm it was possible to obtain the distribution of maximum, minimum and average radius of the pores in porous alumina structures. Additionally, with the calculus of the area occupied by the pores, it was possible to obtain the porosity of the structures. The quantitative results could be obtained and related to the process fabrication characteristics, showing to be reliable and promising to be used to control the pores formation process. Then, this technique could provide a more accurate determination of pore sizes and pores distribution. (C) 2008 Elsevier Ltd. All rights reserved.

Investigation of AISI 1040 steel corrosion H(2)S solution containing chloride ions by digital image processing coupled with in electrochemical techniques

This paper presents a study of AISI 1040 steel corrosion in aqueous electrolyte of acetic acid buffer containing 3.1 and 31 x 10(-3) mol dm(-3) of Na(2)S in both the presence and absence of 3.5 wt.% NaCl. This investigation of steel corrosion was carried out using potential polarization, and open-circuit and in situ optical microscopy. The morphological analysis and classification of types of surface corrosion damage by digital image processing reveals grain boundary corrosion and shows a non-uniform sulfide film growth, which occurs preferentially over pearlitic grains through successive formation and dissolution of the film. (C) 2011 Elsevier Ltd. All rights reserved.

Border figure detection using a phase oscillator network with dynamical coupling

Oscillator networks have been developed in order to perform specific tasks related to image processing. Here we analytically investigate the existence of synchronism in a pair of phase oscillators that are short-range dynamically coupled. Then, we use these analytical results to design a network able of detecting border of black-and-white figures. Each unit composing this network is a pair of such phase oscillators and is assigned to a pixel in the image. The couplings among the units forming the network are also dynamical. Border detection emerges from the network activity.

Effect of image analysis software on neurofunctional activation during processing of emotional human faces

Functional brain imaging techniques such as functional MRI (fMRI) that allow the in vivo investigation of the human brain have been exponentially employed to address the neurophysiological substrates of emotional processing. Despite the growing number of fMRI studies in the field, when taken separately these individual imaging studies demonstrate contrasting findings and variable pictures, and are unable to definitively characterize the neural networks underlying each specific emotional condition. Different imaging packages, as well as the statistical approaches for image processing and analysis, probably have a detrimental role by increasing the heterogeneity of findings. In particular, it is unclear to what extent the observed neurofunctional response of the brain cortex during emotional processing depends on the fMRI package used in the analysis. In this pilot study, we performed a double analysis of an fMRI dataset using emotional faces. The Statistical Parametric Mapping (SPM) version 2.6 (Wellcome Department of Cognitive Neurology, London, UK) and the XBAM 3.4 (Brain Imaging Analysis Unit, Institute of Psychiatry, Kings College London, UK) programs, which use parametric and non-parametric analysis, respectively, were used to assess our results. Both packages revealed that processing of emotional faces was associated with an increased activation in the brain`s visual areas (occipital, fusiform and lingual gyri), in the cerebellum, in the parietal cortex, in the cingulate cortex (anterior and posterior cingulate), and in the dorsolateral and ventrolateral prefrontal cortex. However, blood oxygenation level-dependent (BOLD) response in the temporal regions, insula and putamen was evident in the XBAM analysis but not in the SPM analysis. Overall, SPM and XBAM analyses revealed comparable whole-group brain responses. Further Studies are needed to explore the between-group compatibility of the different imaging packages in other cognitive and emotional processing domains. (C) 2009 Elsevier Ltd. All rights reserved.

A Road Following Approach Using Artificial Neural Networks Combinations

Navigation is a broad topic that has been receiving considerable attention from the mobile robotic community over the years. In order to execute autonomous driving in outdoor urban environments it is necessary to identify parts of the terrain that can be traversed and parts that should be avoided. This paper describes an analyses of terrain identification based on different visual information using a MLP artificial neural network and combining responses of many classifiers. Experimental tests using a vehicle and a video camera have been conducted in real scenarios to evaluate the proposed approach.

Proposal for DICOM Multiframe Medical Image Integrity and Authenticity

This paper presents a novel algorithm to successfully achieve viable integrity and authenticity addition and verification of n-frame DICOM medical images using cryptographic mechanisms. The aim of this work is the enhancement of DICOM security measures, especially for multiframe images. Current approaches have limitations that should be properly addressed for improved security. The algorithm proposed in this work uses data encryption to provide integrity and authenticity, along with digital signature. Relevant header data and digital signature are used as inputs to cipher the image. Therefore, one can only retrieve the original data if and only if the images and the inputs are correct. The encryption process itself is a cascading scheme, where a frame is ciphered with data related to the previous frames, generating also additional data on image integrity and authenticity. Decryption is similar to encryption, featuring also the standard security verification of the image. The implementation was done in JAVA, and a performance evaluation was carried out comparing the speed of the algorithm with other existing approaches. The evaluation showed a good performance of the algorithm, which is an encouraging result to use it in a real environment.

Entropy-Based Approach to Analyze and Classify Mineral Aggregates

This paper presents an automatic method to detect and classify weathered aggregates by assessing changes of colors and textures. The method allows the extraction of aggregate features from images and the automatic classification of them based on surface characteristics. The concept of entropy is used to extract features from digital images. An analysis of the use of this concept is presented and two classification approaches, based on neural networks architectures, are proposed. The classification performance of the proposed approaches is compared to the results obtained by other algorithms (commonly considered for classification purposes). The obtained results confirm that the presented method strongly supports the detection of weathered aggregates.

A novel MAP-MRF approach for multispectral image contextual classification using combination of suboptimal iterative algorithms

In this paper we present a novel approach for multispectral image contextual classification by combining iterative combinatorial optimization algorithms. The pixel-wise decision rule is defined using a Bayesian approach to combine two MRF models: a Gaussian Markov Random Field (GMRF) for the observations (likelihood) and a Potts model for the a priori knowledge, to regularize the solution in the presence of noisy data. Hence, the classification problem is stated according to a Maximum a Posteriori (MAP) framework. In order to approximate the MAP solution we apply several combinatorial optimization methods using multiple simultaneous initializations, making the solution less sensitive to the initial conditions and reducing both computational cost and time in comparison to Simulated Annealing, often unfeasible in many real image processing applications. Markov Random Field model parameters are estimated by Maximum Pseudo-Likelihood (MPL) approach, avoiding manual adjustments in the choice of the regularization parameters. Asymptotic evaluations assess the accuracy of the proposed parameter estimation procedure. To test and evaluate the proposed classification method, we adopt metrics for quantitative performance assessment (Cohen`s Kappa coefficient), allowing a robust and accurate statistical analysis. The obtained results clearly show that combining sub-optimal contextual algorithms significantly improves the classification performance, indicating the effectiveness of the proposed methodology. (C) 2010 Elsevier B.V. All rights reserved.

An Information Theory framework for two-stage binary image operator design

The design of translation invariant and locally defined binary image operators over large windows is made difficult by decreased statistical precision and increased training time. We present a complete framework for the application of stacked design, a recently proposed technique to create two-stage operators that circumvents that difficulty. We propose a novel algorithm, based on Information Theory, to find groups of pixels that should be used together to predict the Output Value. We employ this algorithm to automate the process of creating a set of first-level operators that are later combined in a global operator. We also propose a principled way to guide this combination, by using feature selection and model comparison. Experimental results Show that the proposed framework leads to better results than single stage design. (C) 2009 Elsevier B.V. All rights reserved.

Automatic contour extraction from 2D neuron images

This work describes a novel methodology for automatic contour extraction from 2D images of 3D neurons (e.g. camera lucida images and other types of 2D microscopy). Most contour-based shape analysis methods cannot be used to characterize such cells because of overlaps between neuronal processes. The proposed framework is specifically aimed at the problem of contour following even in presence of multiple overlaps. First, the input image is preprocessed in order to obtain an 8-connected skeleton with one-pixel-wide branches, as well as a set of critical regions (i.e., bifurcations and crossings). Next, for each subtree, the tracking stage iteratively labels all valid pixel of branches, tip to a critical region, where it determines the suitable direction to proceed. Finally, the labeled skeleton segments are followed in order to yield the parametric contour of the neuronal shape under analysis. The reported system was successfully tested with respect to several images and the results from a set of three neuron images are presented here, each pertaining to a different class, i.e. alpha, delta and epsilon ganglion cells, containing a total of 34 crossings. The algorithms successfully got across all these overlaps. The method has also been found to exhibit robustness even for images with close parallel segments. The proposed method is robust and may be implemented in an efficient manner. The introduction of this approach should pave the way for more systematic application of contour-based shape analysis methods in neuronal morphology. (C) 2008 Elsevier B.V. All rights reserved.

Treatment with paracetamol, ketorolac or etoricoxib did not hinder alveolar bone healing: a histometric study in rats

Prostaglandins control osteoblastic and osteoclastic function under physiological or pathological conditions and are important modulators of the bone healing process. The non-steroidal anti-inflammatory drugs (NSAIDs) inhibit cyclooxygenase (COX) activity and consequently prostaglandins synthesis. Experimental and clinical evidence has indicated a risk for reparative bone formation related to the use of non-selective (COX-1 and COX-2) and COX-2 selective NSAIDs. Ketorolac is a non-selective NSAID which, at low doses, has a preferential COX-1 inhibitory effect and etoricoxib is a new selective COX-2 inhibitor. Although literature data have suggested that ketorolac can interfere negatively with long bone fracture healing, there seems to be no study associating etoricoxib with reparative bone formation. Paracetamol/acetaminophen, one of the first choices for pain control in clinical dentistry, has been considered a weak anti-inflammatory drug, although supposedly capable of inhibiting COX-2 activity in inflammatory sites. OBJECTIVE: The purpose of the present study was to investigate whether paracetamol, ketorolac and etoricoxib can hinder alveolar bone formation, taking the filling of rat extraction socket with newly formed bone as experimental model. MATERIAL AND METHODS: The degree of new bone formation inside the alveolar socket was estimated two weeks after tooth extraction by a differential point-counting method, using an optical microscopy with a digital camera for image capture and histometry software. Differences between groups were analyzed by ANOVA after confirming a normal distribution of sample data. RESULTS AND CONCLUSIONS: Histometric results confirmed that none of the tested drugs had a detrimental effect in the volume fraction of bone trabeculae formed inside the alveolar socket.

Avaliação citométrica dos adipócitos localizados no tecido subcutâneo da parede anterior do abdome após infiltração percutânea de CO2

OBJETIVO: Avaliar os efeitos da infiltração de dióxido de carbono em adipócitos presentes na parede abdominal. MÉTODOS: Quinze voluntárias foram submetidas a sessões de infusão de CO2 durante três semanas consecutivas (duas sessões por semana com intervalos de dois a três dias entre cada sessão). O volume de gás carbônico infundido por sessão, em pontos previamente demarcados, foi sempre calculado com base na superfície da área a ser tratada, com volume infundido fixo de 250 mL/100cm² de superfície tratada. Os pontos de infiltração foram demarcados respeitando-se o limite eqüidistante 2cm entre eles. Em cada ponto se injetou 10mL, por sessão, com fluxo de 80mL/min. Foram colhidos fragmentos de tecido celular subcutâneo da parede abdominal anterior antes e após o tratamento. O número e as alterações histomorfológicas dos adipócitos (diâmetro médio, perímetro, comprimento, largura e número de adipócitos por campos de observação) foram mensurados por citometria computadorizada. Os resultados foram analisados com o teste t de Student pareado, adotando-se nível de significância de 5% (p<0,05). RESULTADOS: Encontrou-se redução significativa no número de adipócitos da parede abdominal e na área, diâmetro, perímetro, comprimento e largura após o uso da hipercapnia (p=0,0001). CONCLUSÃO: A infiltração percutânea de CO2 reduz a população e modifica a morfologia dos adipócitos presentes na parede abdominal anterior.

Keratoconus prediction using a finite element model of the cornea with local biomechanical properties

PURPOSE: The ability to predict and understand which biomechanical properties of the cornea are responsible for the stability or progression of keratoconus may be an important clinical and surgical tool for the eye-care professional. We have developed a finite element model of the cornea, that tries to predicts keratoconus-like behavior and its evolution based on material properties of the corneal tissue. METHODS: Corneal material properties were modeled using bibliographic data and corneal topography was based on literature values from a schematic eye model. Commercial software was used to simulate mechanical and surface properties when the cornea was subject to different local parameters, such as elasticity. RESULTS: The simulation has shown that, depending on the corneal initial surface shape, changes in local material properties and also different intraocular pressures values induce a localized protuberance and increase in curvature when compared to the remaining portion of the cornea. CONCLUSIONS: This technique provides a quantitative and accurate approach to the problem of understanding the biomechanical nature of keratoconus. The implemented model has shown that changes in local material properties of the cornea and intraocular pressure are intrinsically related to keratoconus pathology and its shape/curvature.

Resultados preliminares de um sistema de topografia de grande-ângulo usando videoceratógrafo com discos de Plácido

OBJETIVO: Desenvolver a instrumentação e o "software" para topografia de córnea de grande-ângulo usando o tradicional disco de Plácido. O objetivo é permitir o mapeamento de uma região maior da córnea para topógrafos de córnea que usem a técnica de Plácido, fazendo-se uma adaptação simples na mira. MÉTODOS: Utilizando o tradicional disco de Plácido de um topógrafo de córnea tradicional, 9 LEDs (Light Emitting Diodes) foram adaptados no anteparo cônico para que o paciente voluntário pudesse fixar o olhar em diferentes direções. Para cada direção imagens de Plácido foram digitalizadas e processadas para formar, por meio de algoritmo envolvendo elementos sofisticados de computação gráfica, um mapa tridimensional completo da córnea toda. RESULTADOS: Resultados apresentados neste trabalho mostram que uma região de até 100% maior pode ser mapeada usando esta técnica, permitindo que o clínico mapeie até próximo ao limbo da córnea. São apresentados aqui os resultados para uma superfície esférica de calibração e também para uma córnea in vivo com alto grau de astigmatismo, mostrando a curvatura e elevação. CONCLUSÃO: Acredita-se que esta nova técnica pode propiciar a melhoria de alguns processos, como por exemplo: adaptação de lentes de contato, algoritmos para ablações costumizadas para hipermetropia, entre outros.

Computational adjustment technique for digital mammographic images based on the digitizer characteristic curve

We evaluated the performance of a novel procedure for segmenting mammograms and detecting clustered microcalcifications in two types of image sets obtained from digitization of mammograms using either a laser scanner, or a conventional ""optical"" scanner. Specific regions forming the digital mammograms were identified and selected, in which clustered microcalcifications appeared or not. A remarkable increase in image intensity was noticed in the images from the optical scanner compared with the original mammograms. A procedure based on a polynomial correction was developed to compensate the changes in the characteristic curves from the scanners, relative to the curves from the films. The processing scheme was applied to both sets, before and after the polynomial correction. The results indicated clearly the influence of the mammogram digitization on the performance of processing schemes intended to detect microcalcifications. The image processing techniques applied to mammograms digitized by both scanners, without the polynomial intensity correction, resulted in a better sensibility in detecting microcalcifications in the images from the laser scanner. However, when the polynomial correction was applied to the images from the optical scanner, no differences in performance were observed for both types of images. (C) 2008 SPIE and IS&T [DOI: 10.1117/1.3013544]