Análise fractal da vasculatura retínica: métodos de segmentação e de cálculo dimensional

Embora tenha sido proposto que a vasculatura retínica apresenta estrutura fractal, nenhuma padronização do método de segmentação ou do método de cálculo das dimensões fractais foi realizada. Este estudo objetivou determinar se a estimação das dimensões fractais da vasculatura retínica é dependente dos métodos de segmentação vascular e dos métodos de cálculo de dimensão. Métodos: Dez imagens retinográficas foram segmentadas para extrair suas árvores vasculares por quatro métodos computacionais (“multithreshold”, “scale-space”, “pixel classification” e “ridge based detection”). Suas dimensões fractais de “informação”, de “massa-raio” e “por contagem de caixas” foram então calculadas e comparadas com as dimensões das mesmas árvores vasculares, quando obtidas pela segmentação manual (padrão áureo). Resultados: As médias das dimensões fractais variaram através dos grupos de diferentes métodos de segmentação, de 1,39 a 1,47 para a dimensão por contagem de caixas, de 1,47 a 1,52 para a dimensão de informação e de 1,48 a 1,57 para a dimensão de massa-raio. A utilização de diferentes métodos computacionais de segmentação vascular, bem como de diferentes métodos de cálculo de dimensão, introduziu diferença estatisticamente significativa nos valores das dimensões fractais das árvores vasculares. Conclusão: A estimação das dimensões fractais da vasculatura retínica foi dependente tanto dos métodos de segmentação vascular, quanto dos métodos de cálculo de dimensão utilizados

Testu arteko koherentziazko erlazio-egitura: lehen urratsak euskaraz

[EU]Testu bat koherente egiten duten arrazoiak ulertzea oso baliagarria da testuaren beraren ulermenerako, koherentzia eta koherentzia-erlazioak testu bat edo gehiago koherente diren ondorioztatzen laguntzen baitigu. Lan honetan gai bera duten testu ezberdinen arteko koherentziazko 3 Cross Document Structure Theory edo CST (Radev, 2000) erlazio aztertu eta sailkatu dira. Hori egin ahal izateko, euskaraz idatziriko gai berari buruzko testuak segmentatzeko eta beraien arteko erlazioak etiketatzeko gidalerroak proposatzen dira. 10 testuz osaturiko corpusa etiketatu da; horietako 3 cluster bi etiketatzailek aztertu dute. Etiketatzaileen arteko adostasunaren berri ematen dugu. Koherentzia-erlazioak garatzea oso garrantzitsua da Hizkuntzaren Prozesamenduko hainbat sistementzat, hala nola, informazioa erauzteko sistementzat, itzulpen automatikoarentzat, galde-erantzun sistementzat eta laburpen automatikoarentzat. Etorkizunean CSTko erlazio guztiak corpus esanguratsuan aztertuko balira, testuen arteko koherentzia- erlazioak euskarazko testuen prozesaketa automatikoa bideratzeko lehenengo pausua litzateke hemen egindakoa.

Gestão do marketing de relacionamento: um estudo em empresas hoteleiras de Natal - RN

The present study it analyzes the Management of the Marketing of strategy Relationship as distinguishing for the host s companies of the city of Natal - RN. To carry through this analysis interviews with managers had been carried through, as well as the direct comment of processes, documents, actions and strategies developed for the hotels, with intention to know the level of perception and valuation of the relationship with customers, to verify resources and technologies used in the Management of the Relationship Marketing, identification, segmentation and differentiation of customers, personalization of products and services, and results of the emphasis in the relationship with customers for the host s companies. The research can be classified as exploratory - descriptive, and its universe is limited to the city of Natal, having enclosed hotels that have carried through tourist activity in 2005 and 2006. Still on the criteria of election of the sample, the study it investigated host s companies who if fit in the category superior luxury, or either, five stars, pertaining the national nets and international. How much to the treatment and analysis of the data the was made to leave of the theoretical support of the authors who work the thematic one and of the analysis of the interviews with managers, documents and processes observed for the researcher in the studied hotels. The research sample that the interviewed ones understand the importance to work the Management of the Marketing of Relationship in the host s companies me intention to get sustainable competitive advantage. One still evidenced that the searched hotels make use of strategies and instruments of Management of the Marketing of Relationship, however without an ample theoretical knowledge and yes only as base in the experience of the managers and spread processes already, generating one moment competitive advantage and not relationships of long duration

Generating Discriminative Objective Proposals via Submodular Ranking

Object recognition has long been a core problem in computer vision. To improve object spatial support and speed up object localization for object recognition, generating high-quality category-independent object proposals as the input for object recognition system has drawn attention recently. Given an image, we generate a limited number of high-quality and category-independent object proposals in advance and used as inputs for many computer vision tasks. We present an efficient dictionary-based model for image classification task. We further extend the work to a discriminative dictionary learning method for tensor sparse coding. In the first part, a multi-scale greedy-based object proposal generation approach is presented. Based on the multi-scale nature of objects in images, our approach is built on top of a hierarchical segmentation. We first identify the representative and diverse exemplar clusters within each scale. Object proposals are obtained by selecting a subset from the multi-scale segment pool via maximizing a submodular objective function, which consists of a weighted coverage term, a single-scale diversity term and a multi-scale reward term. The weighted coverage term forces the selected set of object proposals to be representative and compact; the single-scale diversity term encourages choosing segments from different exemplar clusters so that they will cover as many object patterns as possible; the multi-scale reward term encourages the selected proposals to be discriminative and selected from multiple layers generated by the hierarchical image segmentation. The experimental results on the Berkeley Segmentation Dataset and PASCAL VOC2012 segmentation dataset demonstrate the accuracy and efficiency of our object proposal model. Additionally, we validate our object proposals in simultaneous segmentation and detection and outperform the state-of-art performance. To classify the object in the image, we design a discriminative, structural low-rank framework for image classification. We use a supervised learning method to construct a discriminative and reconstructive dictionary. By introducing an ideal regularization term, we perform low-rank matrix recovery for contaminated training data from all categories simultaneously without losing structural information. A discriminative low-rank representation for images with respect to the constructed dictionary is obtained. With semantic structure information and strong identification capability, this representation is good for classification tasks even using a simple linear multi-classifier.

Numerical estimation of Carbonate properties using a digital rock physics workflow

Digital rock physics combines modern imaging with advanced numerical simulations to analyze the physical properties of rocks -- In this paper we suggest a special segmentation procedure which is applied to a carbonate rock from Switzerland -- Starting point is a CTscan of a specimen of Hauptmuschelkalk -- The first step applied to the raw image data is a nonlocal mean filter -- We then apply different thresholds to identify pores and solid phases -- Because we are aware of a nonneglectable amount of unresolved microporosity we also define intermediate phases -- Based on this segmentation determine porositydependent values for the pwave velocity and for the permeability -- The porosity measured in the laboratory is then used to compare our numerical data with experimental data -- We observe a good agreement -- Future work includes an analytic validation to the numerical results of the pwave velocity upper bound, employing different filters for the image segmentation and using data with higher resolution

Relación entre atrofia cortical difusa y desempeño cognitivo : estudio en población mayor de 60 años en un hospital universitario en la ciudad de Bogotá

El presente trabajo tuvo como objetivo evaluar la existencia de la relación entre la atrofia cortical difusa objetivada por neuroimagenes cerebrales y desempeños cognitivos determinados mediante la aplicación de pruebas neuropsicológicas que evalúan memoria de trabajo, razonamiento simbólico verbal y memoria anterógrada declarativa. Participaron 114 sujetos reclutados en el Hospital Universitario Mayor Méderi de la ciudad de Bogotá mediante muestreo de conveniencia. Los resultados arrojaron diferencias significativas entre los dos grupos (pacientes con diagnóstico de atrofia cortical difusa y pacientes con neuroimagenes interpretadas como dentro de los límites normales) en todas las pruebas neuropsicológicas aplicadas. Respecto a las variables demográficas se pudo observar que el grado de escolaridad contribuye como factor neuroprotector de un posible deterioro cognitivo. Tales hallazgos son importantes para determinar protocoles tempranos de detección de posible instalación de enfermedades neurodegenerativas primarias.

Effects of meal size and proximal-distal segmentation on gastric activity

AIM: To evaluate the effects of meal size and three segmentations on intragastric distribution of the meal and gastric motility, by scintigraphy. METHODS: Twelve healthy volunteers were randomly assessed, twice, by scintigraphy. The test meal consisted of 60 or 180 mL of yogurt labeled with 64 MBq (99m)Tc-tin colloid. Anterior and posterior dynamic frames were simultaneously acquired for 18 min and all data were analyzed in MatLab. Three proximal-distal segmentations using regions of interest were adopted for both meals. RESULTS: Intragastric distribution of the meal between the proximal and distal compartments was strongly influenced by the way in which the stomach was divided, showing greater proximal retention after the 180 mL. An important finding was that both dominant frequencies (1 and 3 cpm) were simultaneously recorded in the proximal and distal stomach; however, the power ratio of those dominant frequencies varied in agreement with the segmentation adopted and was independent of the meal size. CONCLUSION: It was possible to simultaneously evaluate the static intragastric distribution and phasic contractility from the same recording using our scintigraphic approach. (C) 2010 Baishideng. All rights reserved.

Gene Expression Noise in Spatial Patterning: hunchback Promoter Structure Affects Noise Amplitude and Distribution in Drosophila Segmentation

Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression. This variability must be constrained in the highly reproducible and coordinated events of development. We identify means by which noise is controlled during gene expression by characterizing the dependence of hb mRNA and protein output noise on hb promoter structure and transcriptional dynamics. We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Model parameters are fit to data from WT embryos, the self-regulation mutant hb(14F), and lacZ reporter constructs using different portions of the hb promoter. We have corroborated model noise predictions experimentally. The results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, rather than on Bcd fluctuations. The constructs and mutant, which lack self-regulation, indicate that the multiple Bcd binding sites in the hb promoter (and their strengths) also play a role in buffering noise. The model is robust to the variation in Bcd binding site number across a number of fly species. This study identifies particular ways in which promoter structure and regulatory dynamics reduce hb output noise. Insofar as many of these are common features of genes (e. g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.

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.

Using Reverberation to Improve Range and Elevation Discrimination for Small Array Sound Source Localization

Sound source localization (SSL) is an essential task in many applications involving speech capture and enhancement. As such, speaker localization with microphone arrays has received significant research attention. Nevertheless, existing SSL algorithms for small arrays still have two significant limitations: lack of range resolution, and accuracy degradation with increasing reverberation. The latter is natural and expected, given that strong reflections can have amplitudes similar to that of the direct signal, but different directions of arrival. Therefore, correctly modeling the room and compensating for the reflections should reduce the degradation due to reverberation. In this paper, we show a stronger result. If modeled correctly, early reflections can be used to provide more information about the source location than would have been available in an anechoic scenario. The modeling not only compensates for the reverberation, but also significantly increases resolution for range and elevation. Thus, we show that under certain conditions and limitations, reverberation can be used to improve SSL performance. Prior attempts to compensate for reverberation tried to model the room impulse response (RIR). However, RIRs change quickly with speaker position, and are nearly impossible to track accurately. Instead, we build a 3-D model of the room, which we use to predict early reflections, which are then incorporated into the SSL estimation. Simulation results with real and synthetic data show that even a simplistic room model is sufficient to produce significant improvements in range and elevation estimation, tasks which would be very difficult when relying only on direct path signal components.

Targeted! Population segmentation, electronic surveillance and governing the unemployed in Australia

Targeting is increasingly used to manage people. It operates by segmenting populations and providing different levels of opportunities and services to these groups. Each group is subject to different levels of surveillance and scrutiny. This article examines the deployment of targeting in Australian social security. Three case studies of targeting are presented in Australia's management of benefit overpayment and fraud, the distribution of employment services and the application of workfare. In conceptualizing surveillance as governance, the analysis examines the rationalities, technologies and practices that make targeting thinkable, practicable and achievable. In the case studies, targeting is variously conceptualized and justified by calculative risk discourses, moral discourses of obligation and notions of welfare dependency Advanced information technologies are also seen as particularly important in giving rise to the capacity to think about and act on population segments.

Exploring the knowledge contained in neuroimages: Statistical discriminant analysis and automatic segmentation of the most significant changes

Objective: The aim of this article is to propose an integrated framework for extracting and describing patterns of disorders from medical images using a combination of linear discriminant analysis and active contour models. Methods: A multivariate statistical methodology was first used to identify the most discriminating hyperplane separating two groups of images (from healthy controls and patients with schizophrenia) contained in the input data. After this, the present work makes explicit the differences found by the multivariate statistical method by subtracting the discriminant models of controls and patients, weighted by the pooled variance between the two groups. A variational level-set technique was used to segment clusters of these differences. We obtain a label of each anatomical change using the Talairach atlas. Results: In this work all the data was analysed simultaneously rather than assuming a priori regions of interest. As a consequence of this, by using active contour models, we were able to obtain regions of interest that were emergent from the data. The results were evaluated using, as gold standard, well-known facts about the neuroanatomical changes related to schizophrenia. Most of the items in the gold standard was covered in our result set. Conclusions: We argue that such investigation provides a suitable framework for characterising the high complexity of magnetic resonance images in schizophrenia as the results obtained indicate a high sensitivity rate with respect to the gold standard. (C) 2010 Elsevier B.V. All rights reserved.

A segmentation-based and partial-volume-compensated method for an accurate measurement of lateral ventricular volumes on T-1-weighted magnetic resonance images

Lateral ventricular volumes based on segmented brain MR images can be significantly underestimated if partial volume effects are not considered. This is because a group of voxels in the neighborhood of lateral ventricles is often mis-classified as gray matter voxels due to partial volume effects. This group of voxels is actually a mixture of ventricular cerebro-spinal fluid and the white matter and therefore, a portion of it should be included as part of the lateral ventricular structure. In this note, we describe an automated method for the measurement of lateral ventricular volumes on segmented brain MR images. Image segmentation was carried in combination of intensity correction and thresholding. The method is featured with a procedure for addressing mis-classified voxels in the surrounding of lateral ventricles. A detailed analysis showed that lateral ventricular volumes could be underestimated by 10 to 30% depending upon the size of the lateral ventricular structure, if mis-classified voxels were not included. Validation of the method was done through comparison with the averaged manually traced volumes. Finally, the merit of the method is demonstrated in the evaluation of the rate of lateral ventricular enlargement. (C) 2001 Elsevier Science Inc. All rights reserved.

Modelling and segmentation of the vocal tract during speech production by using deformable models in magnetic resonance images

The first and second authors would like to thank the support of the PhD grants with references SFRH/BD/28817/2006 and SFRH/PROTEC/49517/2009, respectively, from Fundação para a Ciência e Tecnol ogia (FCT). This work was partially done in the scope of the project “Methodologies to Analyze Organs from Complex Medical Images – Applications to Fema le Pelvic Cavity”, wi th reference PTDC/EEA- CRO/103320/2008, financially supported by FCT.

Automated segmentation, tracking and evaluation of bacteria in microscopy images

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica