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Nowadays, image steganography has an important role in hiding information in advanced applications, such as medical image communication, confidential communication and secret data storing, protection of data alteration, access control system for digital content distribution and media database systems. In these applications, one of the most important aspects is to hide information in a cover image whithout suffering any alteration. Currently, all existing approaches used to hide a secret message in a cover image produce some level of distortion in this image. Although these levels of distortion present acceptable PSNR values, this causes minimal visual degradation that can be detected by steganalysis techniques. In this work, we propose a steganographic method based on a genetic algorithm to improve the PSNR level reduction. To achieve this aim, the proposed algorithm requires a private key composed of two values. The first value serves as a seed to generate the random values required on the genetic algorithm, and the second value represents the sequence of bit locations of the secret medical image within the cover image. At least the seed must be shared by a secure communication channel. The results demonstrate that the proposed method exhibits higher capacity in terms of PNSR level compared with existing works.

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Colorectal cancer (CRC) was the second-ranked worldwide type of cancer during 2020 due to the crude mortality rate of 12.0 per 100000 inhabitants. It can be prevented if glandular tissue (adenomatous polyps) is detected early. Colonoscopy has been strongly recommended as a screening test for both early cancer and adenomatous polyps. However, it has some limitations that include the high polyp miss rate for smaller (< 10 mm) or flat polyps, which are easily missed during visual inspection. Due to the rapid advancement of technology, artificial intelligence (AI) has been a thriving area in different fields, including medicine. Particularly, in gastroenterology AI software has been included in computer-aided systems for diagnosis and to improve the assertiveness of automatic polyp detection and its classification as a preventive method for CRC. This article provides an overview of recent research focusing on AI tools and their applications in the early detection of CRC and adenomatous polyps, as well as an insightful analysis of the main advantages and misconceptions in the field.

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The COVID-19 pandemic, which originated in December 2019 in the city of Wuhan, China, continues to have a devastating effect on the health and well-being of the global population. Currently, approximately 8.8 million people have already been infected and more than 465,740 people have died worldwide. An important step in combating COVID-19 is the screening of infected patients using chest X-ray (CXR) images. However, this task is extremely time-consuming and prone to variability among specialists owing to its heterogeneity. Therefore, the present study aims to assist specialists in identifying COVID-19 patients from their chest radiographs, using automated computational techniques. The proposed method has four main steps: (1) the acquisition of the dataset, from two public databases; (2) the standardization of images through preprocessing; (3) the extraction of features using a deep features-based approach implemented through the networks VGG19, Inception-v3, and ResNet50; (4) the classifying of images into COVID-19 groups, using eXtreme Gradient Boosting (XGBoost) optimized by particle swarm optimization (PSO). In the best-case scenario, the proposed method achieved an accuracy of 98.71%, a precision of 98.89%, a recall of 99.63%, and an F1-score of 99.25%. In our study, we demonstrated that the problem of classifying CXR images of patients under COVID-19 and non-COVID-19 conditions can be solved efficiently by combining a deep features-based approach with a robust classifier (XGBoost) optimized by an evolutionary algorithm (PSO). The proposed method offers considerable advantages for clinicians seeking to tackle the current COVID-19 pandemic.

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Uno de los desafíos que los programadores tienen que enfrentar es la alta dimensión de grupos de datos. El proceso de reconocimiento de patrones en imagen y la minería de datos para los volúmenes grandes de información son ejemplos de ellos, optimizar la cantidad de veces que se recorre el conjunto de datos, disminuye el tiempo de procesamiento. Éste documento tiene el objetivo de caracterizar el algoritmo de tres pasos (S3), paralelo a K-medias, como una alternativa para afrontar la alta dimensión del conjunto de datos, en la clasificación no supervisada de imagen. Para el análisis de la concurrencia, se escoge, flujo de datos y el esquema instrucción única con datos múltiples. El resultado obtenido confirma que la concurrencia en ambos es posible, S3 no depende de la selección inicial de los representantes y puede ser el proceso de escogimiento de los primeros vectores centrales en K-medias. S3 es una alternativa a ser tenida en cuenta en la clasificación no supervisada de imágenes médicas y procesos de minería de datos(AU)

One of the challenges to be faced by programmers is the large dimensions of data groups. The process of pattern recognition in images and data mining for great volumes of information is an example. Optimizing the number of times that the set of data is run saves processing time. The purpose of the study was to characterize the three-step (S3) algorithm, parallel to k-means, as an alternative to cope with the large dimension of the data set in unsupervised image classification. Concurrence analysis is based on data flow and the single instruction multiple data scheme. The result obtained confirms that concurrence of both is possible. S3 does not depend on initial selection of representatives, and may be the process for selection of the first central vectors in k-means. S3 is an alternative to be considered in the unsupervised classification of medical images and data mining(AU)

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Automatic and reliable prostate segmentation is an essential prerequisite for assisting the diagnosis and treatment, such as guiding biopsy procedure and radiation therapy. Nonetheless, automatic segmentation is challenging due to the lack of clear prostate boundaries owing to the similar appearance of prostate and surrounding tissues and the wide variation in size and shape among different patients ascribed to pathological changes or different resolutions of images. In this regard, the state-of-the-art includes methods based on a probabilistic atlas, active contour models, and deep learning techniques. However, these techniques have limitations that need to be addressed, such as MRI scans with the same spatial resolution, initialization of the prostate region with well-defined contours and a set of hyperparameters of deep learning techniques determined manually, respectively. Therefore, this paper proposes an automatic and novel coarse-to-fine segmentation method for prostate 3D MRI scans. The coarse segmentation step combines local texture and spatial information using the Intrinsic Manifold Simple Linear Iterative Clustering algorithm and probabilistic atlas in a deep convolutional neural networks model jointly with the particle swarm optimization algorithm to classify prostate and non-prostate tissues. Then, the fine segmentation uses the 3D Chan-Vese active contour model to obtain the final prostate surface. The proposed method has been evaluated on the Prostate 3T and PROMISE12 databases presenting a dice similarity coefficient of 84.86%, relative volume difference of 14.53%, sensitivity of 90.73%, specificity of 99.46%, and accuracy of 99.11%. Experimental results demonstrate the high performance potential of the proposed method compared to those previously published.

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BACKGROUND: Age-related macular degeneration (AMD) is a degenerative ocular disease that develops by the formation of drusen in the macula region leading to blindness. This condition can be detected automatically by automated image processing techniques applied in spectral domain optical coherence tomography (SD-OCT) volumes. The most common approach is the individualized analysis of each slice (B-Scan) of the SD-OCT volumes. However, it ends up losing the correlation between pixels of neighboring slices. The retina representation by topographic maps reveals the similarity of these structures with geographic relief maps, which can be represented by geostatistical descriptors. In this paper, we present a methodology based on geostatistical functions for the automatic diagnosis of AMD in SD-OCT. METHODS: The proposed methodology is based on the construction of a topographic map of the macular region. Over the topographic map, we compute geostatistical features using semivariogram and semimadogram functions as texture descriptors. The extracted descriptors are then used as input for a Support Vector Machine classifier. RESULTS: For training of the classifier and tests, a database composed of 384 OCT exams (269 volumes of eyes exhibiting AMD and 115 control volumes) with layers segmented and validated by specialists were used. The best classification model, validated with cross-validation k-fold, achieved an accuracy of 95.2% and an AUROC of 0.989. CONCLUSION: The presented methodology exclusively uses geostatistical descriptors for the diagnosis of AMD in SD-OCT images of the macular region. The results are promising and the methodology is competitive considering previous results published in literature.

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Introducción: La Imagenología facilita e interpreta las imágenes médicas, parte de la aplicación del método clínico y regresa a él. La dinámica del proceso informacional es de vital importancia basada en el razonamiento clínico aportando elementos ricos al diagnóstico. Se hace necesario vincular intereses y puntos de común en temas importantes de docencia e investigación, para lograr una aptitud profesional superior. Objetivo: Analizar la semiología de las imágenes médicas y proponer una gráfica estructurada que parte de la interpretación clínica hasta el diagnóstico probable, transitando por el conocimiento científico y el razonamiento clínico. Desarrollo: La dinámica del proceso informacional en la especialidad de imagenología obtenida por diferentes vías, resulta primario e indispensable para la información que se va a emitir, basada en la indicación médica que aporta datos de interés clínico para la exploración y diagnóstico. Cada detalle es trascendente, resultando importante insertarlo en la práctica médica habitual. El diagnóstico semiológico topográfico, diferencial y nosológico basado en el razonamiento clínico y asociado a la parábola estructural del diagnóstico clínico-imagenológico como herramienta, favorecen un juicio acertado para los profesionales en la interpretación de las imágenes médicas y elaborar un informe final con calidad interpretativa. Conclusiones: El proceso de formación profesional médica se garantiza de forma organizada, rectorada y metodológicamente bien estructurada, imbricando el razonamiento clínico como un todo lo cual transita de principio a fin por el conocimiento científico con criterios de veracidad y evidencia, hasta lograr un diagnóstico definitivo lo más aproximado posible en el informe final(AU)

Introduction: Imaging facilitates and interprets medical images, part of the application of the clinical method, and returns to it. Dynamics of the informational process is of vital importance, as based on clinical reasoning, providing rich elements for diagnosis. It is necessary to link interests and common points regarding important topics of teaching and research, to achieve higher professional aptitude. Objective: To analyze the semiology of medical images and propose a structured graph that starts from clinical interpretation to probable diagnosis, developed based on scientific knowledge and clinical reasoning. Development: Dynamics of the informational process in the specialty of imaging obtained in different ways is primary and indispensable for the information to be issued, based on the medical indication that provides data of clinical interest for exploration and diagnosis. Every detail is transcendent, and it is important to insert them into the usual medical practice. The topographic, differential and nosological-semiological diagnosis based on clinical reasoning and associated with the structural parabola of the clinical-imaging diagnosis as a tool favors the accurate professional assessment in the interpretation of medical images and the preparation of a final report with interpretive quality. Conclusions: The process of medical professional training is guaranteed in an organized, well-structured way, imbricating clinical reasoning as a whole which goes, from start to end, through scientific knowledge with criteria of truth and evidence, until a definitive diagnosis is achieved, as close as possible in the final report(AU)

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BACKGROUND: Pressure ulcers have become subject of study in recent years due to the treatment high costs and decreased life quality from patients. These chronic wounds are related to the global life expectancy increment, being the geriatric and physical disable patients the principal affected by this condition. Injuries diagnosis and treatment usually takes weeks or even months by medical personel. Using non-invasive techniques, such as image processing techniques, it is possible to conduct an analysis from ulcers and aid in its diagnosis. METHODS: This paper proposes a novel technique for image segmentation based on contrast changes by using synthetic frequencies obtained from the grayscale value available in each pixel of the image. These synthetic frequencies are calculated using the model of energy density over an electric field to describe a relation between a constant density and the image amplitude in a pixel. A toroidal geometry is used to decompose the image into different contrast levels by variating the synthetic frequencies. Then, the decomposed image is binarized applying Otsu's threshold allowing for obtaining the contours that describe the contrast variations. Morphological operations are used to obtain the desired segment of the image. RESULTS: The proposed technique is evaluated by synthesizing a Data Base with 51 images of pressure ulcers, provided by the Centre IGURCO. With the segmentation of these pressure ulcer images it is possible to aid in its diagnosis and treatment. To provide evidences of technique performance, digital image correlation was used as a measure, where the segments obtained using the methodology are compared with the real segments. The proposed technique is compared with two benchmarked algorithms. The results over the technique present an average correlation of 0.89 with a variation of ±0.1 and a computational time of 9.04 seconds. CONCLUSIONS: The methodology presents better segmentation results than the benchmarked algorithms using less computational time and without the need of an initial condition.

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En nuestro país se lucha por la soberanía tecnológica y se impulsa la utilización del software libre. Por esto y con un mejor diseño de las soluciones implementadas por el Centro de Biofísica Médica, el imagis 2.0, como paquete de soluciones de un sistema de almacenamiento y transmisión de imágenes médicas, fue desarrollado bajo la plataforma Linux, haciendo uso de herramientas libres, convirtiéndolo en un sistema más eficiente, estable y robusto. Con este trabajo pretendemos primero realizar un breve recorrido por la historia de los sistemas de almacenamiento y transmisión de imágenes médicas en nuestro país, para luego adentrarnos en una solución implementada bajo plataforma libre que sirve de base a la implementación para especializaciones médicas, exponiendo su uso en los procesos radioterapéuticos(AU)

In our country we fight for technological sovereignty and the use of free software is promoted. For this and with better design solutions implemented by the Center of Medical Biophysics, the imagis 2.0, as a package of solutions of storage and transmission of medical images systems, was developed under the Linux platform, using free tools, making it more efficient, stable and robust. In this paper we first present a brief review of storage and transmission of medical images history in our country, for then get into a deployed under open platform solution that can be using as framework for the implementation for medical specializations, exposing it use in radiotherapeutic procedures(AU)

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Los modelos y simulaciones de los efectos biomecánicos presentes en la arteria aorta, le proporcionan al especialista de la salud una herramienta computacional, que puede ser empleada en la prevención y el tratamiento de las enfermedades cardiovasculares. Es por esto que en la presente investigación se desarrolla un modelo matemático con la finalidad de implementarlo en simulaciones tridimensionales digitales que permitan analizar el comportamiento mecánico de arterias. Primero se describe la metodología utilizada en la construcción de la geometría de la arteria basada en imágenes provenientes de una tomografía axial computarizada, los ensayos experimentales necesarios para la obtención de los parámetros mecánicos requeridos por el modelo y por último su orden fraccional. Con lo que se obtiene una simulación mediante elementos finitos donde se identifican las zonas de mayor concentración de esfuerzos y el campo de desplazamientos. Para poder obtener estos resultados se empleó una formulación novedosa basada en modelos viscoelásticos de orden fraccional donde además se obtuvieron, a través del módulo complejo, los valores requeridos para la simulación.

The modeling and simulation of the biomechanical effects present in the aorta, give the health specialist a computational tool that can be used in the prevention and treatment of cardiovascular diseases. For that reason on this research a mathematical model was developed in order to implement digital dimensional simulations to analyze the mechanical behavior of arteries. First, its described the methodology used in the construction of the geometry of the artery based on images from a CT scan, next the necessary experimental tests to obtain mechanical parameters required by the model and finally his fractional order. Obtaining a finite element simulation where the areas of greatest stress concentration and the displacement field are identified. To obtain these results a novel formulation based on fractional order viscoelastic models was used and the values required for simulation were obtained through the complex modulus.

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O objetivo deste artigo foi avaliar programas de imagens odontológicas disponíveis gratuitamente na internet como ferramentas para prática do cirurgião-dentista e que funcionam em computadores pessoais. Foi realizada uma pesquisa no Medline entre os anos de 2005 a 2014, com enfoque em software utilizado para visualizar imagens tomográficas na Odontologia. Para a pesquisa dos softwares foi realizado busca no site Google e em sites especializados por programas gratuitos disponíveis para windows. Foram utilizados as palavras chaves "free dicom viewer" e "dental software". De acordo com os critérios de inclusão e exclusão três softwares foram analisados. Conhecer a existência de softwares gratuitos e que dão um grande suporte para os profissionais é de extrema importância para a Odontologia atual.

The aim of this study was to review the dental imaging programs available for free on the Internet as tools to practice DDS and running on personal computers. A survey was conducted in Medline from 2005 to 2014, with focus on the software used to view tomographic images in dentistry. A research about the software was done at Google search site and specialized sites for free programs available for Windows. Key words were used "free dicom viewer" and "dental software." According to the criteria of inclusion and exclusion 3 softwares were analyzed. Knowing the existence of free softwares which are able to support professionals improve their jobs is a matter of great importance for the current dentistry.

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INTRODUCCIÓN: las nuevas herramientas informáticas cada vez más influyen en los avances científicos tecnológicos en la esfera de la salud. Una de las áreas de mayor implementación de estas nuevas herramientas de cómputo es sin dudas, la ortopedia, debido en lo fundamental, a la similitud que tiene el cuerpo humano y su estructura ósea con las propiedades de los materiales de ingeniería que permite modelar tejidos y órganos en correspondencia con teorías remodeladoras que predicen su posible comportamiento mecanobiológico. OBJETIVO: describir el comportamiento de una tibia humana ante estímulos externos de torsión. MÉTODOS: se utilizó el Método de los Elementos Finitos implementado en el software profesional ABAQUS/CAE para el cálculo de tensiones y deformaciones presentes en la tibia humana. RESULTADOS: se obtuvo el modelo específico del paciente con síndrome de torsión tibial, a partir de las imágenes médicas de un tomógrafo; las cuales fueron procesadas por ordenador, se utiliza el software de tratamiento de imágenes médicas MIMICS 10.01 para establecer una relación entre la escala de grises (unidades Hounsfield), la densidad ósea y el módulo de Young. CONCLUSIONES: se determinó que el valor correcto de momento torsor estático que debe ser aplicado a este paciente para iniciar el proceso remodelador es de 30 Nm.

INTRODUCTION: new information tools have a growing influence on technological and scientific advances in health care. Orthopedics is one of the areas where new computational tools have been largely implemented, mainly owing to the similarity of the human body and its bone structure to the properties of engineering materials, enabling the modeling of tissues and organs in accordance with remodeling theories predicting their potential mechanobiological behavior. OBJECTIVE: describe the response of a human tibia to external torsion stimuli. METHODS: estimation of tensions and deformities in the human tibia was based on the Finite Element Method incorporated into the professional software Abaqus / CAE. RESULTS: starting from medical tomographic images, a specific model was obtained for a patient with tibial torsion syndrome. The images were computer processed with the medical imaging treatment software MIMICS 10.01 to establish a relationship between the grayscale (Hounsfield units), bone density and Young's modulus. CONCLUSIONS: it was determined that 30 Nm is the correct static torsion moment value to be applied to this patient to start the remodeling process.

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El desarrollo de las tecnologías ha facilitado la creación de soluciones médicas que agilizan las tareas de los especialistas. A través del uso de este tipo de sistemas, consultorios médicos, clínicas, centros de imagen y departamentos de diagnóstico por imágenes pueden tener a gran velocidad servicios de Internet a su alcance y capacidades de archivo que alguna vez fueron solo para los grandes hospitales. La Universidad de las Ciencias Informáticas ha desarrollado la solución alas PACS-RIS, pero este sistema debido a sus características específicas no causa el impacto deseado debido a los grandes costos de tiempo de instalación y configuración, su uso limitado a plataformas propietarias, la necesidad de equipo de altas prestaciones, entre otras causas. Se presenta la propuesta de solución de software desarrollada para la visualización de imágenes médicas. El sistema está diseñado para ofrecer al personal médico, servicios en línea que faciliten la ejecución de sus tareas. Facilita a los especialistas una gama de herramientas básicas para la visualización y procesamiento de imágenes médicas y creación de los reportes de estudios realizados a pacientes. La aplicación fue desarrollada sobre la plataforma .NET 4.0 con lenguajes de programación C#, JavaScript, HTML5, CSS3. Se utilizaron además las librerías jQuery, Knockout y además de MVVM como patrón arquitectónico para la capa de presentación. El sistema se integra a la solución alas PACS-RIS y está diseñada para que finalmente sea utilizada en dispositivos móviles como celulares y Tablet PC(AU)

The actual development of technologies increases the creation of medical solutions that improve the specialist's tasks. Through the usage of this kind of systems, medical institutions, clinics, image centers and image diagnostic departments can use huge speed internet services and storage capacities that once could only have big hospitals. The Informatics Science University has develop the alas PACS-RIS solution, but this system, due to its specific characteristics, didn't cause the wished impact, due to the big time costs of installation and configuration, the limited use under proprietary platforms, the use in high end computers, among others. This paper has the fundamental objective of develop a web application that allows the medical images visualization and management of image studies reports. Presents a software solution developed in .NET 4.0 platform, with programming languages such as: C#, JavaScript, HTML5, CSS3. Also were used the libraries, jQuery, Knockout, and MVVM as architectural pattern for presentation layer. This solution is integrated with alas PACS-RIS system and is designed for the usage in mobile platforms such as: Mobiles and Tablets PC(AU)

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INTRODUCTION: Breast cancer is the second most common type of cancer in the world, being more common among women and representing 22% of all new cancer cases every year. The sooner it is diagnosed, the better the chances of a successful treatment are. Mammography is one way to detect non-palpable tumors that cause breast cancer. However, it is known that the sensitivity of this exam can vary considerably due to factors such as the specialist's experience, the patient's age and the quality of the images obtained in the exam. The use of computational techniques involving artificial intelligence and image processing has contributed more and more to support the specialists in obtaining a more precise diagnosis. METHODS: This paper proposes a methodology that exclusively uses texture analysis to describe features of masses in digitized mammograms. To increase the efficiency of texture feature extraction, the diversity index's capability to detect patterns of species co-occurrence is used. For this purpose, the Gleason and Menhinick indexes are used. Finally, the extracted texture is classified using the Support Vector Machine, looking to differentiate the malignant masses from the benign. RESULTS: The best result was obtained using the Gleason index, with 86.66% accuracy, 90% sensitivity, 83.33% specificity and an area under the ROC Curve (Az) of 0.86. CONCLUSION: Both indexes showed statistically similar performance; however, the Gleason index was slightly superior.

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OBJETIVO: Pesquisar visualizadores de imagens médicas gratuitos disponíveis na internet capazes de funcionar como cliente PACS (picture archiving and communication system) e avaliar suas principais funções e a viabilidade do uso em computadores pessoais. MATERIAIS E MÉTODOS: Foi feita pesquisa, no Google e em sites especializados, por programas gratuitos disponíveis para o Windows. Foram encontrados cerca de 70, sendo 11 capazes de funcionar como cliente PACS, e selecionados seis destes para análise: ClearCanvas Workstation, KPACS, Onis, Synedra View Personal, Mito e Tudor DicomViewer. Com base nas necessidades dos autores, 16 funções foram avaliadas. RESULTADOS: Dos seis programas avaliados, dois possuem 10 das 16 funções avaliadas e um possui apenas duas. Três realizam MPR (reconstrução multiplanar), um realiza MIP (reconstrução por projeção de intensidade máxima), dois realizam VR (renderizações volumétricas), dois funcionam como servidor PACS, dois geram CDs, um realiza fusão de imagens, três permitem utilizar múltiplos monitores e apenas um não é compatível com Windows 7. CONCLUSÃO: Diversos programas gratuitos estão disponíveis e não existe nenhum completo. Cabe ao usuário analisar e selecionar o programa que melhor se enquadra nas suas necessidades, porém, os programas Onis, Synedra e ClearCanvas se destacam, cada um com suas peculiaridades. É totalmente viável o uso de programas gratuitos para o dia-a-dia do radiologista.

OBJECTIVE: To search in the internet for freeware medical image viewers capable of running as a PACS (picture archiving and communication system) client, and to evaluate their main functions as well as the feasibility of their use in personal computers. MATERIALS AND METHODS: The Google search engine and specialized sites were utilized in the search for freeware softwares for Windows. The authors have found about 70 and among them 11 were able to run as PACS clients. Six were selected for analysis: ClearCanvas Workstation, KPACS, Onis, Synedra View Personal, Mito and Tudor DicomViewer. Sixteen functions selected according to the authors' needs were evaluated. RESULTS: Among the six applications, two presented 10 of the 16 functions, and one of them presented only two. Three perform MPR (multiplanar reconstruction), one performs MIP (maximum intensity projection), two perform VR (volume rendering), two can run as a PACS server, two can create CDs, one performs images fusion, three allow the use of multiple monitors and only one is not compatible with Windows 7. CONCLUSION: Although several freeware applications are available, no one of them is complete. It is up to the users to analyze and select the software that best suits their needs. However, Onis, Synedra and ClearCanvas stand out because of their own peculiarities. The use of freeware image viewers is entirely feasible in the radiologists' daily routine.

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OBJETIVO: Neste artigo são descritas a implementação e avaliação de um sistema de gerenciamento de imagens médicas com suporte à recuperação baseada em conteúdo (PACS-CBIR), integrando módulos voltados para a aquisição, armazenamento e distribuição de imagens, e a recuperação de informação textual por palavras-chave e de imagens por similaridade. MATERIAIS E MÉTODOS: O sistema foi implementado com tecnologias para Internet, utilizando-se programas livres, plataforma Linux e linguagem de programação C++, PHP e Java. Há um módulo de gerenciamento de imagens compatível com o padrão DICOM e outros dois módulos de busca, um baseado em informações textuais e outro na similaridade de atributos de textura de imagens. RESULTADOS: Os resultados obtidos indicaram que as imagens são gerenciadas e armazenadas corretamente e que o tempo de retorno das imagens, sempre menor do que 15 segundos, foi considerado bom pelos usuários. As avaliações da recuperação por similaridade demonstraram que o extrator escolhido possibilitou a separação das imagens por região anatômica. CONCLUSÃO: Com os resultados obtidos pode-se concluir que é viável a implementação de um PACS-CBIR. O sistema apresentou-se compatível com as funcionalidades do DICOM e integrável ao sistema de informação local. A funcionalidade de recuperação de imagens similares pode ser melhorada com a inclusão de outros descritores.

OBJECTIVE: The present paper describes the implementation and evaluation of a medical images management system with content-based retrieval support (PACS-CBIR) integrating modules focused on images acquisition, storage and distribution, and text retrieval by keyword and images retrieval by similarity. MATERIALS AND METHODS: Internet-compatible technologies were utilized for the system implementation with freeware, and C++, PHP and Java languages on a Linux platform. There is a DICOM-compatible image management module and two query modules, one of them based on text and the other on similarity of image texture attributes. RESULTS: Results demonstrate an appropriate images management and storage, and that the images retrieval time, always < 15 sec, was found to be good by users. The evaluation of retrieval by similarity has demonstrated that the selected images extractor allowed the sorting of images according to anatomical areas. CONCLUSION: Based on these results, one can conclude that the PACS-CBIR implementation is feasible. The system has demonstrated to be DICOM-compatible, and that it can be integrated with the local information system. The similar images retrieval functionality can be enhanced by the introduction of further descriptors.

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O Instituto do Coração tem envidado esforços para integrar todas as informações clínicas dentro da Instituição. Nos últimos anos o InCor implementou com sucesso um sistema para transmissão, arquivamento, recuperação, processamento e visualização de Imagens Médicas e um Sistema de Informações Hospitalares (HIS) que armazena as informações administrativas e clínicas. A integração desses subsistemas forma o Prontuário Eletrônico do Paciente (PEP). O InCor é um dos seis Institutos que compõem o Hospital das Clínicas da Universidade de São Paulo. Como cada um dos Institutos possui o seu próprio sistema de informações, a troca de informações entre os Institutos é também uma questão muito relevante. Este trabalho apresenta a experiência no desenvolvimento de um Prontuário Eletrônico funcional e completo, que inclui controle de acesso, exames laboratoriais, imagens (estáticas, dinâmicas e 3D), laudos, documentos e mesmo sinais vitais de tempo real. Este artigo também discute a modelagem e implantação de um protótipo de um PEP distribuído e homogêneo. Atualmente, um volume superior a 2,5 TB de imagens DICOM já foi armazenado utilizando a arquitetura proposta. Diariamente, o PEP armazena mais de 5GB de dados e tem uma quantidade de acessos superior a 300 usuários. O sistema de armazenamento permite uma visibilidade de seis meses para acesso imediato e mais de dois anos para acesso automático utilizando uma jukebox

The Heart Institute (InCor) of São Paulo has been committed to the goal of integrating all clinical information within the institution. In the last few years, InCor has successfully created a system for transmission, archiving, retrieval, processing and visualization of Medical Images and a Hospital Information System (HIS) that stores the institution administrative and clinical information. These integrated subsystems form InCor's Electronic Patient Record (EPR). Since InCor is one of the six institutes of the University of São Paulo Medical School Hospital (HC) and each institute has its own information system, exchanging information among the institutes is also a very important issue. This work describes the experience in the effort to develop a functional and comprehensive EPR, which includes access control, lab exams, images (static, dynamic and 3D), clinical reports, documents and even real-time vital signals. This paper addresses also the design and prototype for integration of distributed and heterogeneous EPR. Currently, more than 2.5 TB of DICOM images, have been stored using the proposed architecture. The EPR stores more than 5 GB/day of data and presents more than 300 hits per day. The proposed storage subsystem allow six months of visibility for rapid retrieval (online mode) and more than two years for automatic retrieval using the jukebox

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