25 resultados para 3D ULTRASONOGRAPHY

em Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España


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[ES] Este trabajo propone un sistema de reconstrucción y visualización médica tridimensional (3D) a partir de imágenes bidimensionales de ultrasonido (US), utilizando un equipo convencional bidimensional (2D) de ecografía acoplado a un sistema de localización electromagnético remoto. el atractivo de tal sistema se basa en su bajo costo, en comparación con equipos 3D genuinos, exhibiendo las mismas virtudes que éstos últimos.

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[EN] OBJECTIVE: Our hypothesis is that sonography performed by the rheumatologist in patients with suspected carpal tunnel syndrome (CTS) has higher diagnostic value compared to physical evaluation. METHODS: Adult patients with suspected idiopathic CTS, defined by sensory symptoms over the distribution of the median nerve with or without positive results with the Phalen and/or the Tinel's maneuvers were included. The diagnosis of CTS was indicated by typical symptoms daily for at least 3 months and a positive nerve conduction study. One rheumatologist unaware of the clinical and electrodiagnostic results performed an ultrasound examination of the median nerve for the area ranging from the inlet to the outlet of the carpal tunnel. Mean cross-sectional area at each level, flattening ratio and bowing of flexor retinaculum were obtained. RESULTS: Sixty-eight patients with 105 affected wrists were examined. Tinel's and Phalen's signs had a closer sensitivity (73% and 67% respectively) and specificity (40% and 30% respectively). The best swelling nerve cut-off by sonography was 9.7 mm2 at the tunnel inlet, with a sensitivity of 86%, a specificity of 48% and accuracy of 77%. A 100% positive predictive value was reached with a cross-sectional area of 13 mm2, involving 33 hands (31% of the whole sample). Maximal cross sectional area and the measurement of flexor retinaculum had an accuracy of 72% and 73% respectively. Combination of physical maneuvers and sonography not yielded more accuracy than cross-sectional area itself. CONCLUSION: In patients with clinical history of idiopathic CTS and positive nerve conduction study, sonography performed by the rheumatologist has higher diagnostic value than physical maneuvers.

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[EN] OBJECTIVES: To assess the usefulness of clinical findings, nerve conduction studies and ultrasonography performed by a rheumatologist to predict success in patients with idiopathic carpal tunnel syndrome (CTS) undergoing median nerve release. METHODS: Ninety consecutive patients with CTS (112 wrists) completed a specific CTS questionnaire and underwent physical examination and nerve conduction studies. Ultrasound examination was performed by a rheumatologist who was blind to any patient's data. Outcome variables were improvement >25% in symptoms of the CTS questionnaire and patient's overall satisfaction (5-point Likert scale) at 3 months postoperatively. Success was defined as improvement in both outcome variables. Receiver operating characteristics (ROC) curves and logistic regression analyses were used to assess the best predictive combination of preoperative findings. RESULTS: Success was achieved in 63% of the operated wrists. Utility parameters and area under the ROC curve (AUC) for individual findings was poor, ranging from 0.481 of the nerve conduction study to 0.634 of the cross-sectional area at tunnel outlet. Logistic regression identified the preoperative US parameters as the best predictive variables for success after 3 months. The best predictive combination (AUC=0.708) included a negative Phalen maneuver, plus absence of thenar atrophy, plus less than moderately abnormalities on nerve conduction studies plus a large maximal cross-sectional area along the tunnel by ultrasonography. CONCLUSION: Although cross-sectional area of the median nerve was the only predictor of success after three months of surgical release, isolated preoperative findings are not reliable predictors of success in patients with idiopathic CTS. A combination of findings that include ultrasound improves prediction.

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Máster Universitario en Oceanografía

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Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

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Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

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[ES] La superficie afectada por incendios en Gran Canaria y Tenerife en Agosto de 2007 (aproximadamente 35.060 hectáreas) fue similar a la quemada en los últimos 22 años en todo el Archipiélago Canario. Sin duda, en los momentos clave de incen-dios, cuando la prevención se ha visto desbordada, se impone una planificación y actuación en base a simulaciones predicti-vas que ayuden a minimizar los daños ocasionados. Los gestores virtuales por ordenador pretenden ser herramientas de ayu-da en este propósito. Se presenta un entorno de desarrollo robusto, funcional y flexible encaminado a crear aplicaciones geográficas 3D mul-ticapa centrado, en esta etapa de desarrollo, en la aplicación a un Gestor Virtual de Emergencias1 (Geviemer) con la capaci-dad de simulación y predicción del fuego en incendios forestales. Se ofrece una herramienta de utilidad para el análisis y la toma de decisiones en incendios en Canarias, con una visualización tridimensional que permite la interacción en tiempo real. El entorno, desarrollado con software libre y diseñado en base a una arquitectura por capas permite adaptarlo completa-mente a las necesidades del usuario, ofreciendo un marco abierto a la especialización en aplicaciones concretas. Se analizan en esta comunicación los pormenores del entorno, destacando las características del diseño del software y las particularida-des de Geviemer.

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[EN] This paper describes a wildfire forecasting application based on a 3D virtual environment and a fire simulation engine. A new open source framework is presented for the development of 3D graphics applications over large geographic areas offering high performance 3D visualization and powerful interaction tools for the Geographic Information Systems community. The application includes a remote module that allows simultaneous connection of several users for monitoring a real wildfire event. The user is enabled to simulate and visualize a wildfire spreading on the terrain under conditions of spatial information on topography and fuels along with weather and wind files.

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[EN] This abstract describes the development of a wildfire forecasting plugin using Capaware. Capaware is designed as an easy to use open source framework to develop 3D graphics applications over large geographic areas offering high performance 3D visualization and powerful interaction tools for the Geographic Information Systems (GIS) community.

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[EN] In this paper we present a variational technique for the reconstruction of 3D cylindrical surfaces. Roughly speaking by a cylindrical surface we mean a surface that can be parameterized using the projection on a cylinder in terms of two coordinates, representing the displacement and angle in a cylindrical coordinate system respectively. The starting point for our method is a set of different views of a cylindrical surface, as well as a precomputed disparity map estimation between pair of images. The proposed variational technique is based on an energy minimization where we balance on the one hand the regularity of the cylindrical function given by the distance of the surface points to cylinder axis, and on the other hand, the distance between the projection of the surface points on the images and the expected location following the precomputed disparity map estimation between pair of images. One interesting advantage of this approach is that we regularize the 3D surface by means of a bi-dimensio al minimization problem. We show some experimental results for large stereo sequences.

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[EN] In this paper, we present a vascular tree model made with synthetic materials and which allows us to obtain images to make a 3D reconstruction.We have used PVC tubes of several diameters and lengths that will let us evaluate the accuracy of our 3D reconstruction. In order to calibrate the camera we have used a corner detector. Also we have used Optical Flow techniques to follow the points through the images going and going back. We describe two general techniques to extract a sequence of corresponding points from multiple views of an object. The resulting sequence of points will be used later to reconstruct a set of 3D points representing the object surfaces on the scene. We have made the 3D reconstruction choosing by chance a couple of images and we have calculated the projection error. After several repetitions, we have found the best 3D location for the point.

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[EN] In this paper we present a method for the regularization of 3D cylindrical surfaces. By a cylindrical surface we mean a 3D surface that can be expressed as an application S(l; µ) ! R3 , where (l; µ) represents a cylindrical parametrization of the 3D surface. We built an initial cylindrical parametrization of the surface. We propose a new method to regularize such cylindrical surface. This method takes into account the information supplied by the disparity maps computed between pair of images to constraint the regularization of the set of 3D points. We propose a model based on an energy which is composed of two terms: an attachment term that minimizes the difference between the image coordinates and the disparity maps and a second term that enables a regularization by means of anisotropic diffusion. One interesting advantage of this approach is that we regularize the 3D surface by using a bi-dimensional minimization problem.

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[EN] In this paper, we present a vascular tree model made with synthetic materials and which allows us to obtain images to make a 3D reconstruction. In order to create this model, we have used PVC tubes of several diameters and lengths that will let us evaluate the accuracy of our 3D reconstruction. We have made the 3D reconstruction from a series of images that we have from our model and after we have calibrated the camera. In order to calibrate it we have used a corner detector. Also we have used Optical Flow techniques to follow the points through the images going and going back. Once we have the set of images where we have located a point, we have made the 3D reconstruction choosing by chance a couple of images and we have calculated the projection error. After several repetitions, we have found the best 3D location for the point.