Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

Supporting content-based image retrieval and computer-aided diagnosis systems with association rule-based techniques

In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.

An association rule-based method to support medical image diagnosis with efficiency

In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.

Padronização de um método para mensuração das tábuas ósseas vestibular e lingual dos maxilares na Tomografia Computadorizada de Feixe Cônico (Cone Beam)

INTRODUÇÃO: a espessura das tábuas ósseas que recobrem os dentes por vestibular e lingual constitui um dos fatores limitantes da movimentação dentária. O avanço tecnológico em Imaginologia permitiu avaliar detalhadamente essas regiões anatômicas por meio da utilização da tomografia computadorizada de feixe cônico (TCFC). OBJETIVO: descrever e padronizar, pormenorizadamente, um método para mensuração das tábuas ósseas vestibular e lingual dos maxilares nas imagens de tomografia computadorizada de feixe cônico. METODOLOGIA: a padronização digital da posição da imagem da face deve constituir o primeiro passo antes da seleção dos cortes de TCFC. Dois cortes axiais de cada maxilar foram empregados para a mensuração da espessura do osso alveolar vestibular e lingual. Utilizou-se como referência a junção cemento-esmalte dos primeiros molares permanentes, tanto na arcada superior quanto na inferior. RESULTADOS: cortes axiais paralelos ao plano palatino foram indicados para avaliação quantitativa do osso alveolar na maxila. Na arcada inferior, os cortes axiais devem ser paralelos ao plano oclusal funcional. CONCLUSÃO: o método descrito apresenta reprodutibilidade para utilização em pesquisas, assim como para a avaliação clínica das repercussões periodontais da movimentação dentária, ao permitir a comparação de imagens pré e pós-tratamento.

Juvenile idiopathic arthritis with involvement of the temporomandibular joint: the role of image examinations

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.

Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.

Evaluation of a simple hyphenated system for flow injection solid-phase pre-concentration and capillary electrophoresis

In this work, the development and evaluation of a hyphenated flow injection-capillary electrophoresis system with on-line pre-concentration is described. Preliminary tests were performed to investigate the influence of flow rates over the analytical signals. Results revealed losses in terms of sensitivity of the FIA-CE system when compared to the conventional CE system. To overcome signal decrease and to make the system more efficient, a lower flow rate was set and an anionic resin column was added to the flow manifold in order to pre-concentrate the analyte. The pre-concentration FIA-CE system presented a sensitivity improvement of about 660% and there was only a small increase of 8% in total peak dispersion. These results have confirmed the great potential of the proposed system for many analytical tasks especially for low concentration samples.

Hydrodynamics and suspended sediment transport in the Camboriú estuary - Brazil: pre jetty conditions

Estuarine hydrodynamics is a key factor in the definition of the filtering capacity of an estuary and results from the interaction of the processes that control the inlet morphodynamics and those that are acting in the mixing of the water in the estuary. The hydrodynamics and suspended sediment transport in the Camboriú estuary were assessed by two field campaigns conducted in 1998 that covered both neap and spring tide conditions. The period measured represents the estuarine hydrodynamics and sediment transport prior to the construction of the jetty in 2003 and provides important background information for the Camboriú estuary. Each field campaign covered two complete tidal cycles with hourly measurements of currents, salinity, suspended sediment concentration and water level. Results show that the Camboriú estuary is partially mixed with the vertical structure varying as a function of the tidal range and tidal phase. The dynamic estuarine structure can be balanced between the stabilizing effects generated by the vertical density gradient, which produces buoyancy and stratification flows, and the turbulent effects generated by the vertical velocity gradient that generates vertical mixing. The main sediment source for the water column are the bottom sediments, periodically resuspended by the tidal currents. The advective salt and suspended sediment transport was different between neap and spring tides, being more complex at spring tide. The river discharge term was important under both tidal conditions. The tidal correlation term was also important, being dominant in the suspended sediment transport during the spring tide. The gravitational circulation and Stokes drift played a secondary role in the estuarine transport processes.

Origem e distribuição dos nervos isquiáticos do preá

O preá do semiárido nordestino (Galea spixii Wagler, 1831) é um roedor pertencente à família Caviidae. Pouca literatura é encontrada sobre essa espécie em relação a sua morfologia e seu comportamento ambiental e reprodutivo. Com o objetivo de entender a morfologia geral, em foco, na inervação do membro pélvico dessa espécie, neste trabalho, foi explorado o nervo isquiático, o qual é o maior de todos os nervos do organismo. Foram utilizados 10 preás (cinco machos e cinco fêmeas) que vieram a óbito por causas naturais, oriundos do Centro de Multiplicação de Animais Silvestres da Universidade Federal Rural do Semiárido (CEMAS/UFERSA). Os animais foram fixados após o óbito em solução aquosa de formaldeído 10% e, após 48 horas de imersão nessa solução, foram dissecados para exposição do nervo isquiático. Dessa forma, os dados obtidos foram compilados em tabelas e expressos em desenhos esquemáticos e fotografias. Os pares de nervos isquiáticos originaram-se de raízes ventrais de L6L7S1 (70%) e de L7S1S2 (30%) e distribuíram-se pelos músculos glúteo profundo, bíceps femural, semitendinoso e semimembranoso.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

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.

Decision theory applied to image quality control in radiology

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.

Synergistic effect of simvastatin and ezetimibe on lipid and pro-inflammatory profiles in pre-diabetic subjects

Background: Ezetimibe specifically blocks the absorption of dietary and biliary cholesterol and plant sterols. Synergism of ezetimibe-statin therapy on LDL-cholesterol has been demonstrated, but data concerning the pleiotropic effects of this combination are controversial. Objective: This open-label trial evaluated whether the combination of simvastatin and ezetimibe also results in a synergistic effect that reduces the pro-inflammatory status of pre-diabetic subjects. Methods: Fifty pre-diabetic subjects were randomly assigned to one of 2 groups, one receiving ezetimibe (10 mg/day), the other, simvastatin (20 mg/d) for 12 weeks, followed by an additional 12-week period of combined therapy. Blood samples were collected at baseline, 12 and 24 weeks. RESULTS: Total cholesterol, LDL-cholesterol and apolipoprotein B levels decreased in all the periods analyzed (p < 0.01), but triglycerides declined significantly only after combined therapy. Both drugs induced reductions in C-reactive protein, reaching statistical significance after combining ezetimibe with the simvastatin therapy (baseline 0.59 +/- 0.14, simvastatin monotherapy 0.48 +/- 0.12 mg/dL and 0.35 +/- 0.12 mg/dL, p < 0.023). Such a reduction was independent of LDL-cholesterol change. However, mean levels of TNF-alpha and interleukin-6 and leukocyte count did not vary during the whole study. Conclusion: Expected synergistic lowering effects of a simvastatin and ezetimibe combination on LDL-cholesterol, apolipoprotein B and triglycerides levels were confirmed in subjects with early disturbances of glucose metabolism. We suggest an additive effect of this combination also on inflammatory status based on the reduction of C-reactive protein. Attenuation of pro-inflammatory conditions may be relevant in reducing cardiometabolic risk.

Nutritional status of pre-school children from low income families

Background: We evaluated growth and nutritional status of preschool children between 2 and 6 years old from low income families from 14 daycare centers. Methods: Cross-sectional study with 1544 children from daycare centers of Santo Andre, Brazil. Body weight (W), height (H) and body mass index (BMI) were classified according to the 2000 National Center for Health Statistics (CDC/NCHS). Cutoff points for nutritional disorders: -2 z scores and 2.5 and 10 percentiles for malnutrition risk, 85 to 95 percentile for overweight and above BMI 95 percentile for obesity. Stepwise Forward Regression method was used including age, gender, birth weight, breastfeeding duration, age of mother at birth and period of time they attended the daycare center. Results: Children presented mean z scores of H, W and BMI above the median of the CDC/NCHS reference. Girls were taller and heavier than boys, while we observed similar BMI between both genders. The z scores tended to rise with age. A Pearson Coefficient of Correlation of 0.89 for W, 0.93 for H and 0.95 for BMI was documented indicating positive association of age with weight, height and BMI. The frequency of children below -2 z scores was lower than expected: 1.5% for W, 1.75% for H and 0% for BMI, which suggests that there were no malnourished children. The other extremity of the distribution evidenced prevalence of overweight and obesity of 16.8% and 10.8%, respectively. Conclusion: Low income preschool children are in an advanced stage of nutritional transition with a high prevalence of overweight.

Genetic parameters for pre-weaning traits in Braunvieh cattle

The objective of this study was to estimate genetic parameters for pre-weaning traits of Braunvieh cattle raised under tropical conditions in Brazil. The weight and weight gain parameters were birth weight (BW, N = 9955), weight at 120 days of age (W120, N = 5901), weaning weight at 205 days (WW, N = 6970), weight gain from birth to 205 days (GAIN205, N = 6013), weight gain from birth to 120 days (GAIN120, N = 5135), and weight gain from 120 to 205 days (GAIN85, N = 4482). Variance components were estimated using the animal model with the MTDFREML software. The relationship matrix included 35,188 animals; phenotypic measures were available for 18,688. Direct and maternal heritability increased from birth to weaning, with estimates of 0.23 +/- 0.037, 0.25 +/- 0.050, 0.41 +/- 0.059 for direct heritability for BW, W120 and WW, respectively, 0.08 +/- 0.012, 0.15 +/- 0.032, 0.22 +/- 0.036 for maternal genetic effects, and 0.18, 0.14 and 0.16 for total heritability estimates. For pre-weaning gains, estimates of heritability were 0.36 +/- 0.059, 0.30 +/- 0.059, 0.12 +/- 0.035 for direct genetic effects of the traits GAIN205, GAIN120 and GAIN85, respectively, 0.23 +/- 0.038, 0.17 +/- 0.037, 0.03 +/- 0.029 for estimates of maternal heritability, and 0.12, 0.13, 0.16 for total heritability, respectively. Genetic correlations between weights were greater between measures taken at shorter intervals. This information can be used to optimize the design of programs for genetic improvement of Braunvieh cattle raised under tropical conditions.