Complementary use of priors for pulmonary imaging with electrical impedance and ultrasound computed tomography.

For medical professionals caring for patients undergoing mechanical ventilation due to respiratory failure, the ability to quickly and safely obtain images of pulmonary function at the patient's bedside would be highly desirable. Such images could be used to provide early warnings of developing pulmonary pathologies in real time, thereby reducing the incidence of complications and improving patient outcomes. Electrical impedance tomography (EIT) and low-frequency ultrasound computed tomography (USCT) are two imaging techniques with the potential to provide real-time non-ionizing pulmonary monitoring in the ICU setting, and each method has its own unique advantages as well as drawbacks. In this work, we describe a new algorithm for a system in which the strengths of the two modalities are combined in a complementary fashion. Specifically, preliminary reconstructions from each modality are used as priors to stabilize subsequent reconstructions, providing improved spatial resolution, sharper organ boundaries, and enhanced appearance of pathologies and other features. Results are validated using three numerically simulated thoracic phantoms representing pulmonary pathologies.

Approaches to segment stent area from Intravascular Optical Coherence Tomography

Abstract Introduction Cardiovascular diseases (CVD) have been the focus of research in recent years due to its high mortality rate. It is estimated that 17.5 million people died of CVD in 2012, from which 7.4 million were due to coronary heart disease (CHD). In order to monitor CHD patients and avoid waste of specialists' time, this study proposes the development of a method that segments the area contained by stent struts from Frequency Domain Intravascular Optical Coherence Tomography (the latest technology to view vessels internally) of coronary arteries. Methods The novelty of this study is to find areas comprised by stent struts using two optimal strategies that are robust even with false positives and false negatives detection of stent struts. The first one uses an ellipse fitting algorithm and the other uses a cylinder fitting algorithm. Results Both strategies obtained similar accuracy results close to 98% of true positives, but the cylinder technique showed a run time of at least 50 times higher than the ellipse technique. Conclusion The methods were executed on 443 images with different characteristics showing robustness and usefulness in the medical area.

Realistic deformable 3D numeric phantom for transcutaneous ultrasound

Abstract Introduction Numerical phantoms are important tools to design, calibrate and evaluate several methods in various image-processing applications, such as echocardiography and mammography. We present a framework for creating ultrasound numerical deformable phantoms based on Finite Element Method (FEM), Linear Isomorphism and Field II. The proposed method considers that the scatterers map is a property of the tissue; therefore, the scatterers should move according to the tissue strain. Methods First, a volume representing the target tissue is loaded. Second, parameter values, such as Young’s Modulus, scatterers density, attenuation and scattering amplitudes are inserted for each different regions of the phantom. Then, other parameters related to the ultrasound equipment, such as ultrasound frequency and number of transducer elements, are also defined in order to perform the ultrasound acquisition using Field II. Third, the size and position of the transducer and the pressures that are applied against the tissue are defined. Subsequently, FEM is executed and deformation is computed. Next, 3D linear isomorphism is performed to displace the scatterers according to the deformation. Finally, Field II is carried out to generate the non-deformed and deformed ultrasound data. Results The framework is evaluated by comparing strain values obtained the numerical simulation and from the physical phantom from CIRS. The mean difference between both phantoms is lesser than 10%. Conclusion The acoustic and deformation outcomes are similar to those obtained using a physical phantom. This framework led to a tool, which is available online and free of charges for educational and research purposes.

Atherosclerotic plaque characterization using plaque area variation in IVUS images during compression: a computational investigation

INTRODUCTION: The rupture of atherosclerotic plaques causes millions of death yearly. It is known that the kind of predominant tissue is associated with its dangerousness. In addition, the mechanical properties of plaques have been proved to be a good parameter to characterize the type of tissue, important information for therapeutic decisions. METHODS: Therefore, we present an alternative and simple way to discriminate tissues. The procedure relies on computing an index, the ratio of the plaque area variation of a suspecting plaque, using images acquired with vessel and plaques, pre and post-deformation, under different intraluminal pressure. Numerical phantoms of coronary cross-sections with different morphological aspects, and simulated with a range of properties, were used for evaluation. RESULTS: The outcomes provided by this index and a widely used one were compared, so as to measure their correspondence. As a result, correlations up to 99%, a strong agreement with Bland-Altman and very similar histograms between the two indices, have shown a good level of equivalence between the methods. CONCLUSION: The results demonstrated that the proposed index discriminates highly lipidic from fibro-lipidic and calcified tissues in many situations, as good as the widely used index, yet the proposed method is much simpler to be computed.

Automatic lumen segmentation in IVOCT images using binary morphological reconstruction.

BACKGROUND: Atherosclerosis causes millions of deaths, annually yielding billions in expenses round the world. Intravascular Optical Coherence Tomography (IVOCT) is a medical imaging modality, which displays high resolution images of coronary cross-section. Nonetheless, quantitative information can only be obtained with segmentation; consequently, more adequate diagnostics, therapies and interventions can be provided. Since it is a relatively new modality, many different segmentation methods, available in the literature for other modalities, could be successfully applied to IVOCT images, improving accuracies and uses. METHOD: An automatic lumen segmentation approach, based on Wavelet Transform and Mathematical Morphology, is presented. The methodology is divided into three main parts. First, the preprocessing stage attenuates and enhances undesirable and important information, respectively. Second, in the feature extraction block, wavelet is associated with an adapted version of Otsu threshold; hence, tissue information is discriminated and binarized. Finally, binary morphological reconstruction improves the binary information and constructs the binary lumen object. RESULTS: The evaluation was carried out by segmenting 290 challenging images from human and pig coronaries, and rabbit iliac arteries; the outcomes were compared with the gold standards made by experts. The resultant accuracy was obtained: True Positive (%) = 99.29 ± 2.96, False Positive (%) = 3.69 ± 2.88, False Negative (%) = 0.71 ± 2.96, Max False Positive Distance (mm) = 0.1 ± 0.07, Max False Negative Distance (mm) = 0.06 ± 0.1. CONCLUSIONS: In conclusion, by segmenting a number of IVOCT images with various features, the proposed technique showed to be robust and more accurate than published studies; in addition, the method is completely automatic, providing a new tool for IVOCT segmentation.

Segmentação do lúmen em imagens de IOCT usando Fuzzy Connectedness e Reconstrução Binária Morfológica / Lumen Segmentation in IOCT images using Fuzzy and Binary Morphological Reconstruction

No ano 2010, doenças cardiovasculares (CVD) causaram 33% do total das mortes no Brasil. Tomografia Ótica Coerente Intravascular (IOCT) é uma tecnologia que oferece imagens in vivo para detecção e monitoramento da progressão de CVD. O exame de IOCT permite mais precisão no diagnóstico; contudo, ainda é pequena a variedade de métodos quantitativos aplicados a IOCT na literatura, em comparação à outras modalidades relacionadas. Portanto neste trabalho é proposto um método de segmentação do lúmen, baseado em uma combinação de Fuzzy Connectedness, com múltiplas funções de afinidade, e Operações Morfológicas. As funções de afinidade usadas neste trabalho são: (I) Clássica, (II) Pesos Dinâmicos e (III) Bhattacharyya. Esta última é baseada no coeficiente de Bhattacharyya, utilizado habitualmente para speckle tracking. Primeiro, características não desejadas da imagem são atenuadas. Depois, informações da parede do vaso são obtidas utilizando Fuzzy Connectedness e um processo de binarização dinâmico. Finalmente, operações morfológicas são realizadas para melhorar o lúmen segmentado. Para avaliar o método proposto, um conjunto de 130 imagens advindas de humanos, porcos, e coelhos foram segmentadas e comparadas com seus respectivos "Gold Standards" feitos por especialistas. Uma média de verdadeiros positivos (TP%) = 98,08 e de falsos positivos (FP%) = 2,34 foram obtidas. Com isso, o método proposto resultou em uma maior eficácia do que os estudos publicados anteriormente, encorajando seu uso.

In 2010 cardiovascular disease (CVD) caused 33% of the total deaths in Brazil. Intravascular Optical Coherent Tomography (IOCT) is an imaging technology that provides in vivo detection and monitoring of the progression of coronary heart disease. IOCT exam allows more accurate diagnoses; nonetheless, the set of quantitative methods applied to IOCT in the literature is small compared to other related modalities. Therefore, the proposed approach presents a lumen segmentation method, based on a combination of Fuzzy Connectedness, with multiple affinity functions, and Morphological Operations. The affinity functions used in this work are: (I) classical, (II) Dynamic weights (III) Bhattacharyya. The latter is based on the Bhattacharyya coefficient, commonly used for speckle tracking. Firstly, unwanted features of the image are attenuated. Then, vessel-wall information is obtained using Fuzzy Connectedness and dynamic binarization process. Finally, morphological operations are performed to improve the segmented lumen. To evaluate the proposed method, a set of 130 images from humans, pigs and rabbits were segmented and compared to their corresponding gold standard made by experts. An average of true positive (TP%) = 98.08, and false positive (FP%) = 2.34 were obtained. Hence, the use of the proposed method is suggested since it has yielded higher efficiency than previously published studies.

Processamento de estruturas tridimensionais de Medicina Nuclear na modalidade PET / Processing of three-dimensional structures of Nuclear Medicine in PET modality

A Medicina Nuclear, como especialidade de obtenção de imagens médicas é um dos principais procedimentos utilizados hoje nos centros de saúde, tendo como grande vantagem a capacidade de analisar o comportamento metabólico do paciente. Este projeto está baseado em imagens médicas obtidas através da modalidade PET (Positron Emission Tomography). Para isso, foi desenvolvida uma estrutura de processamento de imagens tridimensionais PET, constituída por etapas sucessivas que se iniciam com a obtenção das imagens padrões (gold standard), sendo utilizados para este fim volumes simulados do Ventrículo Esquerdo do Coração criadas como parte do projeto, assim como phantoms gerados com o software NCAT-4D. A seguir, nos volumes simulados é introduzido ruído Poisson que é o ruído característico das imagens PET. Na sequência é executada uma etapa de pré-processamento, utilizando alguns filtros 3D tais como o filtro da mediana, o filtro da Gaussiana ponderada e o filtro Anscombe/Wiener. Posteriormente é aplicada a etapa de segmentação, processo baseado na teoria de Conectividade Fuzzy sendo implementadas quatro diferentes abordagens 3D: Algoritmo Genérico, LIFO, kTetaFOEMS e Pesos Dinâmicos. Finalmente, um procedimento de avaliação conformado por três parâmetros (Verdadeiro Positivo, Falso Positivo e Máxima Distância) foi utilizado para mensurar o nível de eficiência e precisão do processo. Constatou-se que o par Filtro - Segmentador constituído pelo filtro Anscombe/Wiener junto com o segmentador Fuzzy baseado em Pesos Dinâmicos proporcionou os melhores resultados, com taxas de VP e FP na ordem de 98,49 ± 0,27% e 2,19 ± 0,19%, respectivamente, para o caso do volume do Ventrículo Esquerdo simulado. Com o conjunto de escolhas feitas ao longo da estrutura de processamento, encerrou-se o projeto analisando um número reduzido de volumes pertencentes a um exame PET real, obtendo-se a quantificação dos volumes.

The Nuclear medicine, as a specialty to obtain medical images is very important, and it has became one of the main procedures utilized in Health Care Centers to analyze the metabolic behavior of the patient. This project was based on medical images obtained by the PET modality (Positron Emission Tomography). Thus, we developed a framework for processing Nuclear Medicine three-dimensional images of the PET modality, which is composed of consecutive steps that start with the generation of standard images (gold standard) by using simulated images of the Left Ventricular Heart, such as phantoms obtained from the NCAT-4D software. Then, Poisson quantum noise was introduced into the whole volume to simulate the characteristic noises in PET images. Subsequently, the pre-processing step was executed by using specific 3D filters, such as the median filter, the weighted Gaussian filter, and the Anscombe/Wiener filter. Then the segmentation process, which is based on the Fuzzy Connectedness theory, was implemented. For that purpose four different 3D approaches were implemented: Generic, LIFO, kTetaFOEMS, and Dynamic Weight algorithm. Finally, an assessment procedure was used as a measurement tool to quantify three parameters (True Positive, False Positive and Maximum Distance) that determined the level of efficiency and precision of our process. It was found that the pair filter - segmenter formed by the Anscombe/Wiener filter together with the Fuzzy segmenter based on Dynamic Weights provided the best results, with VP and FP rates of 98.49 ± 0.27% and 2.19 ± 0.19%, respectively, for the simulation of the Left Ventricular volume. Along with the set of choices made during the processing structure, the project was finished with the analysis of a small number of volumes that belonged to a real PET test, thus the quantification of the volumes was obtained.

Realistic IVUS image generation in different intraluminal pressures.

Intravascular ultrasound (IVUS) phantoms are important to calibrate and evaluate many IVUS imaging processing tasks. However, phantom generation is never the primary focus of related works; hence, it cannot be well covered, and is usually based on more than one platform, which may not be accessible to investigators. Therefore, we present a framework for creating representative IVUS phantoms, for different intraluminal pressures, based on the finite element method and Field II. First, a coronary cross-section model is selected. Second, the coronary regions are identified to apply the properties. Third, the corresponding mesh is generated. Fourth, the intraluminal force is applied and the deformation computed. Finally, the speckle noise is incorporated. The framework was tested taking into account IVUS contrast, noise and strains. The outcomes are in line with related studies and expected values. Moreover, the framework toolbox is freely accessible and fully implemented in a single platform.

Adequação de modelo compartimental para exames de tomografia por emissão de pósitrons / Adequacy of compartmental model for positron emission tomography examinations

O presente trabalho objetiva a seleção do modelo compartimental mais adequado ao estudo da dinâmica fisiológica em exames de tomografia por emissão de pósitrons (PET). Para tanto, propõe-se utilizar o critério de informação de Akaike para a seleção do modelo, e a metodologia de equações de sensibilidade e o algoritmo de Levenberg-Marquardt para a tarefa de estimação de parâmetros característicos e, consequentemente, do erro residual da estimativa. São consideradas três estruturas compartimentais compostas, respectivamente, por dois compartimentos e duas constantes características, três compartimentos e quatro constantes características e quatro compartimentos e seis constantes características. Os dados considerados neste trabalho foram sintetizados preocupando-se em reunir as principais características de um exame de tomografia real, tais como tipo e nível de ruído e morfologia de função de excitação do sistema. Aplicando-se a metodologia proposta em três níveis de ruído (baixo, médio e alto), obteve-se concordância do melhor modelo em graus forte e considerável (com índices de Kappa iguais a 0,95, 0,93 e 0,63, respectivamente). Observou-se que, com elevado nível de ruído e modelos mais complexos (quatro compartimentos), a classificação se deteriora devido ao pequeno número de dados para a decisão. Foram desenvolvidos programas e uma interface gráfica que podem ser utilizados na investigação, elaboração, simulação, estimativa de parâmetros e identificação do modelo compartimental para apoio e análise de diagnósticos clínicos e práticas científicas.

The objective of this work is the determination of the most adequate compartmental model for the study of physiological dynamics based on positron emission tomography (PET) exams. We propose the use of Akaike’s information criterion for the optimal model selection, and Levenberg-Marquardt algorithm with sensitivity equations for the task of estimating the characteristic parameters of the differential equations describing the models. We have considered three compartmental structures represented, respectively, by two compartments and two characteristic constants, three compartments and four characteristic constants and four compartments and six characteristics constants. The data considered in this work were synthesized taking into account key features of a real tomography exam, such as type and level of noise and morphology of the input function of the system. Applying the proposed methodology with three noise levels (low, medium and high), we obtained agreement of the best model with strong and considerable degrees (with Kappa indexes equal to  0.95, 0.93 and  0.63, respectively). It was observed that, with high noise level and more complex models (four compartments), the classification is deteriorated due to lack of data for the decision. Programs have been developed and a graphical interface that can be used in research, development, simulation and parameter identification of compartmental models, supporting analysis of clinical diagnostics and scientific practices.

Automatic coronary wall segmentation in intravascular ultrasound images using binary morphological reconstruction.

Intravascular ultrasound (IVUS) image segmentation can provide more detailed vessel and plaque information, resulting in better diagnostics, evaluation and therapy planning. A novel automatic segmentation proposal is described herein; the method relies on a binary morphological object reconstruction to segment the coronary wall in IVUS images. First, a preprocessing followed by a feature extraction block are performed, allowing for the desired information to be extracted. Afterward, binary versions of the desired objects are reconstructed, and their contours are extracted to segment the image. The effectiveness is demonstrated by segmenting 1300 images, in which the outcomes had a strong correlation to their corresponding gold standard. Moreover, the results were also corroborated statistically by having as high as 92.72% and 91.9% of true positive area fraction for the lumen and media adventitia border, respectively. In addition, this approach can be adapted easily and applied to other related modalities, such as intravascular optical coherence tomography and intravascular magnetic resonance imaging.

An approach to automatically segment the media-adventitia borders in IVUS / Uma associação de técnicas para segmentação automática da fronteira da média-adventícia em IVUS

Por ser capaz de mostrar aspectos morfológicos e patológicos de ateroscleroses, o Ultrassom Intravascular (IVUS) se tornou uma das modalidades de imagens médicas mais confiáveis e empregadas em intervenções cardíacas. As características de sua imagem aumentam as chances de um bom diagnóstico, resultando em terapias mais precisas. O estudo de segmentação da fronteira média-adventícia, dentre muitas aplicações, é importante para o aprendizado das propriedades mecânicas e determinação de algumas medidas específicas (raio, diâmetro, etc.) em vasos e placas. Neste trabalho, uma associação de técnicas de processamento de imagens está sendo proposta para atingir alta acurácia na segmentação da borda média-adventícia. Para tanto, foi feita uma combinação das seguintes técnicas: Redução do Speckle por Difusão Anisotrópica (SRAD), Wavelet, Otsu e Morfologia Matemática. Primeiramente, é usado SRAD para atenuar os ruídos speckle. Posteriormente, é executada Transformada Wavelet para extração das características dos vasos e placas. Uma versão binarizada dessas características é criada na qual o limiar ótimo é definido por Otsu. Finalmente, é usada Morfologia Matemática para obtenção do formato da adventícia. O método proposto é avaliado ao segmentar 100 imagens de alta complexidade, obtendo uma média de Verdadeiro Positivo (TP(%)) = 92,83 ± 4,91, Falso Positivo (FP(%)) = 3,43 ± 3,47, Falso Negativo (FN(%)) = 7,17 ± 4,91, Máximo Falso Positivo (MaxFP(mm)) = 0,27 ± 0,22, Máximo Falso Negativo (MaxFN(mm)) = 0,31 ± 0,2. A eficácia do nosso método é demonstrada, comparando este resultado com outro trabalho recente na literatura.

By being able to show morphological and pathological aspects of atherosclerosis, the Intravascular Ultrasound (IVUS) be¬came one of the most reliable and employed medical imaging modality in cardiac interventions. Its image characteristics in¬crease the chances of a good diagnostic, resulting in a precise therapy. The study of media-adventitia borders segmentation in IVUS, among many applications, is important for learning about the mechanical properties and determining some specific measurements (radius, diameter, etc.) in vases and plaques. An approach is proposed to achieve high accuracy in media-adventitia borders segmentation, by making a combination of different image processing operations: Speckle Reducing Anisotropic Diffusion (SRAD), Wavelet, Otsu and Mathematical Morphology. Firstly, SRAD is applied to attenuate the speckle noise. Next, the vessel and plaque features are extracted by performing Wavelet Transform. Optimal thresholding is car¬ried out by Otsu method to create a binarized version of these features. Then, Mathematical Morphology operations are used to obtain an adventitia shape. The proposed approach is evaluated by segmenting 100 challenging images, obtaining an average of True Positive (TP(%)) = 92.83 ± 4.91, False Positive (FP(%)) = 3.43 ± 3.47, False Negative (FN(%)) = 7.17 ± 4.91, Max False Positive (MaxFP(mm)) = 0.27 ± 0.22, Max False Negative (MaxFN(mm)) = 0.31 ± 0.2. The effectiveness of our approach is demonstrated by comparing this result with another recent work in the literature.

Assessing the scientific research productivity of a Brazilian healthcare institution: a case study at the Heart Institute of São Paulo, Brazil.

INTRODUCTION: The present study was motivated by the need to systematically assess the research productivity of the Heart Institute (InCor), Medical School of the University of São Paulo, Brazil. OBJECTIVE: To explore methodology for the assessment of institutional scientific research productivity. MATERIALS AND METHODS: Bibliometric indicators based on searches for author affiliation of original scientific articles or reviews published in journals indexed in the databases Web of Science, MEDLINE, EMBASE, LILACS and SciELO from January 2000 to December 2003 were used in this study. The retrieved records were analyzed according to the index parameters of the journals and modes of access. The number of citations was used to calculate the institutional impact factor. RESULTS: Out of 1253 records retrieved from the five databases, 604 original articles and reviews were analyzed; of these, 246 (41%) articles were published in national journals and 221 (90%) of those were in journals with free online access through SciELO or their own websites. Of the 358 articles published in international journals, 333 (93%) had controlled online access and 223 (67%) were available through the Capes Portal of Journals. The average impact of each article for InCor was 2.224 in the period studied. CONCLUSION: A simple and practical methodology to evaluate the scientific production of health research institutions includes searches in the LILACS database for national journals and in MEDLINE and the Web of Science for international journals. The institutional impact factor of articles indexed in the Web of Science may serve as a measure by which to assess and review the scientific productivity of a research institution.

Assessing the scientific research productivity of a Brazilian healthcare institution: a case study at the heart institute of São Paulo, Brazil

INTRODUCTION: The present study was motivated by the need to systematically assess the research productivity of the Heart Institute (InCor), Medical School of the University of São Paulo, Brazil.OBJECTIVE: To explore methodology for the assessment of institutional scientific research productivity. MATERIALS AND METHODS: Bibliometric indicators based on searches for author affiliation of original scientific articles or reviews published in journals indexed in the databases Web of Science, MEDLINE, EMBASE, LILACS and SciELO from January 2000 to December 2003 were used in this study. The retrieved records were analyzed according to the index parameters of the journals and modes of access. The number of citations was used to calculate the institutional impact factor. RESULTS: Out of 1253 records retrieved from the five databases, 604 original articles and reviews were analyzed; of these, 246 (41%) articles were published in national journals and 221 (90%) of those were in journals with free online access through SciELO or their own websites. Of the 358 articles published in international journals, 333 (93%) had controlled online access and 223 (67%) were available through the Capes Portal of Journals. The average impact of each article for InCor was 2.224 in the period studied. CONCLUSION: A simple and practical methodology to evaluate the scientific production of health research institutions includes searches in the LILACS database for national journals and in MEDLINE and the Web of Science for international journals. The institutional impact factor of articles indexed in the Web of Science may serve as a measure by which to assess and review the scientific productivity of a research institution.

Providing integrity and authenticity in DICOM images: a novel approach.

The increasing adoption of information systems in healthcare has led to a scenario where patient information security is more and more being regarded as a critical issue. Allowing patient information to be in jeopardy may lead to irreparable damage, physically, morally, and socially to the patient, potentially shaking the credibility of the healthcare institution. Medical images play a crucial role in such context, given their importance in diagnosis, treatment, and research. Therefore, it is vital to take measures in order to prevent tampering and determine their provenance. This demands adoption of security mechanisms to assure information integrity and authenticity. There are a number of works done in this field, based on two major approaches: use of metadata and use of watermarking. However, there still are limitations for both approaches that must be properly addressed. This paper presents a new method using cryptographic means to improve trustworthiness of medical images, providing a stronger link between the image and the information on its integrity and authenticity, without compromising image quality to the end user. Use of Digital Imaging and Communications in Medicine structures is also an advantage for ease of development and deployment.

A contextual medical image viewer.

The conventional visualization of medical images is not enough for a rich and comprehensive electronic healthcare record. We believe that it is necessary to provide a viewer with more advanced capabilities than those of regular medical image viewers. In this paper, we propose an architecture that allows the use of contextual information to assist the healthcare professional in his regular tasks. The proposed architecture for the context is composed of an ontology describing the hospital and an inference engine. The result is a Java-based implementation of the architecture, named Dynamic N-dimensional Image Viewer, (ODIN in Portuguese) that is able to adapt its behavior according to the contextual information.

Multilingual information retrieval in thoracic radiology: feasibility study.

Most essential information contained in the electronic medical record is stored as text, and this imposes several difficulties on automated data extraction and retrieval. Natural language processing is an approach that can unlock clinical information from free texts. The proposed methodology uses the specialized natural language processor MEDLEE developed for the English language. To use this processor on Portuguese medical texts, chest X-ray reports were machine translated (MT) into English. The result of serial coupling of MT and NLP is tagged text that needs further investigation for extracting clinical findings. This experiment's objective was to investigate normal reports and reports with device description on a set of 165 chest X-ray reports. We obtained sensitivity and specificity of 1 and 0.71 for the first condition, and 0.97 and 0.97 for the second. The reference was formed by the opinions of two radiologists. The results of this experiment indicate the viability of extracting clinical findings from chest X-ray reports through coupling MT and NLP.

Segurança em informações médicas: visão introdutória e panorama atual / Security in medical information: overview and current scenario

Com a disseminação dos sistemas informatizados para a área da saúde, a questão da segurança da informação passa a assumir uma importância cada vez mais crucial, visando principalmente resguardar um dos direitos fundamentais do paciente, qual seja, a privacidade das suas informações acerca da saúde da pessoa pode acarretar danos irreparáveis de ordem física e moral. Além disso, o comprometimento da confiabilidade de tais informações pode minar a credibilidade das instituições de saúde e prejudicar a pesquisa, na medida em que dados incorretos levarão naturalmente a diagnósticos e resultados incorretos. Apesar da relevância que a segurança possui, o desenvolvimento de soluções voltadas para a área médica é algo relativamente recente. Isso porque existem várias características específicas para esta área, o que requer uma visão sobre o contexto das informações médicas - em particular, os asapectos éticos e legais - para que se possa atender de forma adequada os seus requisitos e implantar os mecanismos tecnológicos condizentes. Este artigo apresenta um panorama geral da segurança em informações médicas, fazendo primeiramente algumas considerações chave sobre a segurança da informação de um modo geral e o contexto de segurança na área médica, para então mostrar asa propostas e implementações realizadas em várias frentes visando garantir os diferentes aspectos da segurança das informações médicas.

Rede de alta velocidade para a transmissão, armazenamento e visualização de imagens médicas / High Speed Networks for Transmission, Storage and Viewing of Medical Images

A distribuição dos serviços de saúde e o compartilhamento de informações clínicas, utilizando sistemas de telecomunicação, envolvem um conjunto diverso e complexo de tecnologias. Além disso, se a informação a ser compartilhada contém imagens, um problema especial em cardiologia é como distribuir imagens dinâmicas obtidas em estudos de ecocardiografia e de angiografia com qualidade de serviço. As imagens individuais são facilmente transmitidas, mas o volume total, considerando todas as imagens em uma seqüência, é enorme podendo chegar facilmente na ordem de Giga Bytes por paciente. Os avanços em tecnologias de comunicações e em informática facilitam a médicos e especialistas localizados em um centro de referência a troca de informações com médicos e profissionais de saúde em local distante, em outro centro, ou mesmo com o próprio paciente. Embora em especialidades como cardiologia, radiologia e patologia, as informações relevantes sobre o paciente sejam inerentemente digitais, a necessidade de alta qualidade associada ao volume de dados impõem limitações na prática de ações de Medicina à distância através dos meios de comunicação convencionais

Avaliaçäo do pré-processamento das projeçöes em ESPECT com phantom físico / Evaluation of projections pre-processing in SPECT with physical phantom

Neste trabalho, apresenta-se uma solução alternativa para a reconstrução de imagens tomográficas em Medicina Nuclear que usa o modelo de ruído de Poisson. O algoritmo proposto foi aplicado a um phantom físico e comparada com a metodologia usual de reconstrução em rotina clínica. A análise dos resultados mostrou que a aplicação do método melhora a qualidade das imagens reconstruídas.

We present an altemative solution for the reconstruction of SPECT images using a Poisson Noise Model. The proposed algorithm was applied on a real phantom and compared to the standard clinica! procedure. Results have shown that the proposed method improves the quality ofthe SPECT images.

Determinaçäo automática das regiöes de interesse em estudos de ventriculografia radioisotópica / Automatic determination of regions of interest in radioisotopic ventriculography studies

Apresentamos um método para a determinação automática das regiões de interesse em estudos de ventriculografia radioisotópica (VR). O método utiliza informações a priori sobre a localização do ventrículo esquerdo (VE), além de uma versão modificada do operador Lapraciano da Guassiana conjugado com operações de morfologia matemática. O algoritmo apresenta boa correlação com o procedimento manual, além de ser rápido e robusto.

We present a method for the automatic determination of regions of interest in gated blood pool studies. The method uses a priori information about left ventricle location, and a modified version of the Laplacian of Gaussian operator is applied with some mathematical morphology operations, yielding the final regions. The algorithm showed to be highly correlated to the manual procedure, besides being to be fast and robust.