Sistemas de microscopía virtual: análisis y perspectivas

Microscopy has been constantly evolving since the end of the Twentieth Century, with the introduction of new resources which have improved its practice. For example, the use of the virtual microscope has reached a high level of maturity; it is a synergy among disciplines such as pathology, histology, medical informatics and image analysis. This technology has moved forward many paradigms in research, diagnosis, education and medical training. The virtual microscopy systems require the digitalization of a physical slide, using motorized microscopes, pre and post image processing, compression, transmission and visualization. This article provides an extensive analysis of each of these processes. The main characteristics of virtual microscopy are presented as well as the impact of these systems in image interpretation and in diagnostic activities.Desde finales del siglo XX la microscopía se ha venido transformando, incluyendo nuevos recursos que mejoran y perfeccionan su práctica. Entre ellos se destaca el microscopio virtual, la sinergia entre disciplinas como la patología, la histología, la informática médica y el análisis de imágenes. Esta tecnología ha cambiado muchos paradigmas en la investigación, el diagnóstico, la educación y el entrenamiento médico. Los sistemas de microscopía virtual requieren de la digitalización de una placa con el uso de microscopios robotizados, antes del procesamiento de la imagen y después de él, compresión, transmisión por la red y visualización. En este artículo se hace un análisis extenso de cada uno de estos procesos, y se presentan las principales características de los microscopios virtuales, junto con el impacto de estos sistemas en actividades de interpretación y diagnóstico

Management of spatial data for visualization on mobile devices

Vector-based mapping is emerging as a preferred format in Location-based Services(LBS), because it can deliver an up-to-date and interactive map visualization. The Progressive Transmission(PT) technique has been developed to enable the ecient transmission of vector data over the internet by delivering various incremental levels of detail(LoD). However, it is still challenging to apply this technique in a mobile context due to many inherent limitations of mobile devices, such as small screen size, slow processors and limited memory. Taking account of these limitations, PT has been extended by developing a framework of ecient data management for the visualization of spatial data on mobile devices. A data generalization framework is proposed and implemented in a software application. This application can signicantly reduce the volume of data for transmission and enable quick access to a simplied version of data while preserving appropriate visualization quality. Using volunteered geographic information as a case-study, the framework shows exibility in delivering up-to-date spatial information from dynamic data sources. Three models of PT are designed and implemented to transmit the additional LoD renements: a full scale PT as an inverse of generalisation, a viewdependent PT, and a heuristic optimised view-dependent PT. These models are evaluated with user trials and application examples. The heuristic optimised view-dependent PT has shown a signicant enhancement over the traditional PT in terms of bandwidth-saving and smoothness of transitions. A parallel data management strategy associated with three corresponding algorithms has been developed to handle LoD spatial data on mobile clients. This strategy enables the map rendering to be performed in parallel with a process which retrieves the data for the next map location the user will require. A viewdependent approach has been integrated to monitor the volume of each LoD for visible area. The demonstration of a exible rendering style shows its potential use in visualizing dynamic geoprocessed data. Future work may extend this to integrate topological constraints and semantic constraints for enhancing the vector map visualization

Motion prediction for caching and prefetching in mouse-driven DVE navigation

A distributed virtual environment (DVE) allows geographically separated users to participate in a shared virtual environment via connected networks. However, when the users are connected by the Internet, bandwidth limitation and network latency may seriously affect the performance and the interactivity of the system. This explains why there are very few DVE applications for the Internet. To address these shortcomings, caching and prefetching techniques are usually employed. Unfortunately, the effectiveness of these techniques depends largely on the accuracy of the prediction method used. Although there are a few methods proposed for predicting 3D motion, most of them are primarily designed for predicting the motion of specific objects by assuming certain object motion behaviors. We notice that in desktop DVE applications, such as virtual walkthrough and network gaming, the 2D mouse is still the most popular device used for navigation input. Through studying the motion behavior of a mouse during 3D navigation, we have developed a hybrid motion model for predicting the mouse motion during such navigation—a linear model for prediction at low-velocity motion and an elliptic model for prediction at high-velocity motion. The predicted mouse motion velocity is then mapped to the 3D environment for predicting the user’s 3D motion. We describe how this prediction method can be integrated into the caching and prefetching mechanisms of our DVE prototype.We also demonstrate the effectiveness of the method and the resulting caching and prefetching mechanisms through extensive experiments