941 resultados para Digital mammographic images


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Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.

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This paper presents an approach to ameliorate the reliability of the correspondence points relating two consecutive images of a sequence. The images are especially difficult to handle, since they have been acquired by a camera looking at the sea floor while carried by an underwater robot. Underwater images are usually difficult to process due to light absorption, changing image radiance and lack of well-defined features. A new approach based on gray-level region matching and selective texture analysis significantly improves the matching reliability

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A common problem in video surveys in very shallow waters is the presence of strong light fluctuations, due to sun light refraction. Refracted sunlight casts fast moving patterns, which can significantly degrade the quality of the acquired data. Motivated by the growing need to improve the quality of shallow water imagery, we propose a method to remove sunlight patterns in video sequences. The method exploits the fact that video sequences allow several observations of the same area of the sea floor, over time. It is based on computing the image difference between a given reference frame and the temporal median of a registered set of neighboring images. A key observation is that this difference will have two components with separable spectral content. One is related to the illumination field (lower spatial frequencies) and the other to the registration error (higher frequencies). The illumination field, recovered by lowpass filtering, is used to correct the reference image. In addition to removing the sunflickering patterns, an important advantage of the approach is the ability to preserve the sharpness in corrected image, even in the presence of registration inaccuracies. The effectiveness of the method is illustrated in image sets acquired under strong camera motion containing non-rigid benthic structures. The results testify the good performance and generality of the approach

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In order to develop applications for z;isual interpretation of medical images, the early detection and evaluation of microcalcifications in digital mammograms is verg important since their presence is often associated with a high incidence of breast cancers. Accurate classification into benign and malignant groups would help improve diagnostic sensitivity as well as reduce the number of unnecessa y biopsies. The challenge here is the selection of the useful features to distinguish benign from malignant micro calcifications. Our purpose in this work is to analyse a microcalcification evaluation method based on a set of shapebased features extracted from the digitised mammography. The segmentation of the microcalcifications is performed using a fixed-tolerance region growing method to extract boundaries of calcifications with manually selected seed pixels. Taking into account that shapes and sizes of clustered microcalcifications have been associated with a high risk of carcinoma based on digerent subjective measures, such as whether or not the calcifications are irregular, linear, vermiform, branched, rounded or ring like, our efforts were addressed to obtain a feature set related to the shape. The identification of the pammeters concerning the malignant character of the microcalcifications was performed on a set of 146 mammograms with their real diagnosis known in advance from biopsies. This allowed identifying the following shape-based parameters as the relevant ones: Number of clusters, Number of holes, Area, Feret elongation, Roughness, and Elongation. Further experiments on a set of 70 new mammogmms showed that the performance of the classification scheme is close to the mean performance of three expert radiologists, which allows to consider the proposed method for assisting the diagnosis and encourages to continue the investigation in the sense of adding new features not only related to the shape

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A new approach to mammographic mass detection is presented in this paper. Although different algorithms have been proposed for such a task, most of them are application dependent. In contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. In this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. Two different databases were used to show the robustness of the approach. The first one consisted on a set of 160 regions of interest (RoIs) extracted from the MIAS database, being 40 of them with confirmed masses and the rest normal tissue. The second set of RoIs was extracted from the DDSM database, and contained 196 RoIs containing masses and 392 with normal, but suspicious regions. Initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach

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Videos, text and links on how to get files from various sources from screen, webpage, digital cameras etc.

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This webpage provides links to image banks and sources of photos which are usable for educational purposes.

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Introducción: El desarrollo del archivo docente de imágenes diagnósticas, permite al Departamento de Imágenes compartir y difundir el conocimiento de la colección de casos e imágenes radiológicas reales con mayor rapidez y facilidad en el acceso a las mismas por parte de todo el personal de la Clínica Fundación Cardio-Infantil – Instituto de Cardiología, a través por portal web “e-cardio”, contribuyendo así en la formación académica del personal médico, técnico y administrativo. Metodología: Este trabajo no responde a ningún tipo de estudio epidemiológico, sino a una colección de imágenes y reseñas radiológicas de casos de patología torácica y cardiovascular, procedentes de pacientes de la Fundación Cardioinfantil – Instituto de Cardiología, con el fin de conformar un archivo digital docente. Resultados: Se recolectaron 1.148 radiografías impresas, previamente rotuladas según el Index for Radiological Diagnoses 4 edición y de archivos individuales 3.512 imágenes. Utilizando los criterios de inclusión y exclusión, se realizó la selección de imágenes para continuar el procedimiento. Se descartaron 278 radiografías impresas por no tener rotulo, estar en mal estado general, o rotulación incorrecta. En el caso de los archivos digitales, se descartaron 1435 imágenes, utilizando el mismo procedimiento. Conclusión: Iniciar la conformación y montaje del primer archivo docente de la Clínica Fundación Cardioinfantil – Instituto de Cardiología. Motivar a los profesionales médicos de la Clínica Fundación Cardio Infantil, y especialmente a los residentes de Radiología, para que estén en un proceso de aprendizaje continúo, fortaleciendo su autoevaluación, y todo ello para beneficio final de los pacientes y de la misma Institución.

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Introducción. Las imágenes obtenidas mediante rayos X, determinan una conducta clínica en ortopedia y son analizadas por parte del cirujano en el momento previo a realizar un acto quirúrgico. El planeamiento pre quirúrgico basado en radiografías de cadera, permite predecir el tamaño de los componentes protésicos a utilizar en un reemplazo de cadera. Con el advenimiento de las radiografías digitales, existe la falsa percepción de que estas tienen corregido el factor de magnificación. La corrección de dicho factor requiere un protocolo de calibración de imágenes, aún no implementado en la Fundación Santa Fe de Bogotá (FSFB). Como consecuencia, las radiografías de cadera actualmente resultan magnificadas. Materiales y métodos. Fueron seleccionados 73 pacientes con reemplazo articular total de la cadera intervenidos en la FSFB. Para cada paciente, se estableció la dimensión de la cabeza protésica en la radiografía de cadera obtenida mediante el sistema de radiología digital (PACS-IMPAX) y su tamaño fue comparado con el de la cabeza femoral implantada. Resultados. La concordancia entre los dos observadores al medir la dimensión radiológica de los componentes protésicos fue excelente y el coeficiente de magnificación promedio de 1.2 (20%). Este será introducido al PACS-IMPAX para ajustar el tamaño definitivo de la radiografía. Conclusión. El ajuste del PACS-IMPAX permite obtener radiografías en las cuales se refleja con mayor precisión el tamaño de los segmentos anatómicos y de los componentes protésicos.

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Introducción: La DSA es el método de elección para el seguimiento de pacientes con aneurismas intracraneales embolizados; esta se puede asociar a complicaciones incapacitantes o mortales. La MRA se ha propuesto como método alternativo por menor costo y menos morbi-mortalidad, aunque su desempeño diagnóstico permanece en discusión debido al desarrollo de nuevos protocolos, resonadores más potentes y nuevas aplicaciones de la DSA. Metodología: Exploramos la literatura hasta la actualidad y comparamos el desempeño diagnóstico de la MRA con la DSA para detectar flujo residual posterior a la embolización terapéutica de aneurismas intracraneales. Realizamos una revisión sistemática de la literatura y meta-análisis basados en 34 artículos detectados en la búsqueda que incluyó las bases de datos PubMed, Scopus, ScIELO y BVS. Resultados: La TOF-MRA demostró sensibilidad de 86.8% (84.3%-89.1%) y especificidad de 91.2% (89%-93.1%); la SROC para TOF-MRA demostró un AUC de 0.95. El desempeño de la CE-MRA demostró sensibilidad de 88.1% (84.6%-91.1%) y especificidad de 89.1% (85.7%-91.9%); la SROC presentó una AUC de 0.93. El análisis estratificado por potencia del resonador encontró que la TOF-MRA tiene mejor desempeño con el resonador de 3T, aunque no es estadísticamente significativo. La concordancia interobservador con TOF-MRA y CE-MRA fue moderada a muy buena. Discusión: El desempeño diagnóstico de la MRA en el seguimiento de aneurismas intracraneales embolizados demostró ser bueno, con sensibilidad mayor a 84%, siendo ligeramente mejor con TOF-MRA, sin lograr reemplazar la DSA. Sin embargo, los resultados deben ser evaluados con precaución por la heterogeneidad de los resultados de los estudios incluidos. (Abreviaturas: DSA: Angiografía por Sustracción Digital; MRA: Angiografía por Resonancia Magnética; TOF-MRA: Angiorresonancia por Tiempo de Vuelo; CE-MRA: Angiorresonancia contrastada).

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Resumen basado en el de la publicación

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Resumen basado en el de la publicación

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The distributions of times to first cell division were determined for populations of Escherichia coli stationary-phase cells inoculated onto agar media. This was accomplished by using automated analysis of digital images of individual cells growing on agar and calculation of the "box area ratio." Using approximately 300 cells per experiment, the mean time to first division and standard deviation for cells grown in liquid medium at 37 degrees C and inoculated on agar and incubated at 20 degrees C were determined as 3.0 h and 0.7 h, respectively. Distributions were observed to tail toward the higher values, but no definitive model distribution was identified. Both preinoculation stress by heating cultures at 50 degrees C and postinoculation stress by growth in the presence of higher concentrations of NaCl increased mean times to first division. Both stresses also resulted in an increase in the spread of the distributions that was proportional to the mean division time, the coefficient of variation being constant at approximately 0.2 in all cases. The "relative division time," which is the time to first division for individual cells expressed in terms of the cell size doubling time, was used as measure of the "work to be done" to prepare for cell division. Relative division times were greater for heat-stressed cells than for those growing under osmotic stress.

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This paper presents a new method to calculate sky view factors (SVFs) from high resolution urban digital elevation models using a shadow casting algorithm. By utilizing weighted annuli to derive SVF from hemispherical images, the distance light source positions can be predefined and uniformly spread over the whole hemisphere, whereas another method applies a random set of light source positions with a cosine-weighted distribution of sun altitude angles. The 2 methods have similar results based on a large number of SVF images. However, when comparing variations at pixel level between an image generated using the new method presented in this paper with the image from the random method, anisotropic patterns occur. The absolute mean difference between the 2 methods is 0.002 ranging up to 0.040. The maximum difference can be as much as 0.122. Since SVF is a geometrically derived parameter, the anisotropic errors created by the random method must be considered as significant.

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Understanding Digital Literacies provides an accessible and timely introduction to new media literacies. It supplies readers with the theoretical and analytical tools with which to explore the linguistic and social impact of a host of new digital literacy practices. Each chapter in the volume covers a different topic, presenting an overview of the major concepts, issues, problems and debates surrounding the topic, while also encouraging students to reflect on and critically evaluate their own language and communication practices. Features include: coverage of a diverse range of digital media texts, tools and practices including blogging, hypertextual organisation, Facebook, Twitter, YouTube, Wikipedia, websites and games an extensive range of examples and case studies to illustrate each topic, such as how blogs have affected our thinking about communication, how the creation and sharing of digital images and video can bring about shifts in social roles, and how the design of multiplayer online games for children can promote different ideologies a variety of discussion questions and mini-ethnographic research projects involving exploration of various patterns of media production and communication between peers, for example in the context of Wikinomics and peer production, social networking and civic participation, and digital literacies at work end of chapter suggestions for further reading and links to key web and video resources a companion website providing supplementary material for each chapter, including summaries of key issues, additional web-based exercises, and links to further resources such as useful websites, articles, videos and blogs.