José Antonio Iglesias Guitián

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We present an adaptive out-of-core technique for rendering massive scalar volumes employing single pass GPU raycasting. The method is based on the decomposition of a volumetric dataset into small cubical bricks, which are then organized into an octree structure maintained out-of-core. The octree contains the original data at the leaves, and a filtered(More)
We present a GPU accelerated volume ray casting system interactively driving a multiuser light field display. The display, driven by a single programmable GPU, is based on a specially arranged array of projectors and a holographic screen and provides full horizontal parallax. The characteristics of the display are exploited to develop a specialized volume(More)
Large scale and structurally complex volume datasets from high-resolution 3D imaging devices or computational simulations pose a number of technical challenges for interactive visual analysis. In this paper, we present the first integration of a multiscale volume representation based on tensor approximation within a GPU-accelerated out-of-core(More)
We report on a light-field display based virtual environment enabling multiple naked-eye users to perceive detailed multi-gigavoxel volumetric models as floating in space, responsive to their actions, and delivering different information in different areas of the workspace. Our contributions include a set of specialized interactive illustrative techniques(More)
We present a novel multiresolution compression-domain GPU volume rendering architecture designed for interactive local and networked exploration of rectilinear scalar volumes on commodity platforms. In our approach, the volume is decomposed into a multiresolution hierarchy of bricks. Each brick is further subdivided into smaller blocks, which are compactly(More)
Despite the ability of current GPU processors to treat heavy parallel computation tasks, its use for solving medical image segmentation problems is still not fully exploited and remains challenging. A lot of difficulties may arise related to, for example, the different image modalities, noise and artifacts of source images, or the shape and appearance(More)
We present a prototype medical data visualiza-tion system exploiting a light field display and custom direct volume rendering techniques to enhance understanding of massive volumetric data, such as CT, MRI, and PET scans. The system can be integrated with standard medical image archives and extends the capabilities of current radiology workstations by(More)
Figure 1: Our biophysically-based model allows to reproduce the changes in the optical properties of skin due to aging, which greatly affects its appearance. Structural changes and varying chromophore concentrations yield changes in the scattering and absorption coefficients, producing paler and slightly more translucent skin. The image shows examples for(More)
We propose a new adaptive rendering algorithm that enhances the performance of Monte Carlo ray tracing by reducing the noise, i.e., variance, while preserving a variety of high-frequency edges in rendered images through a novel prediction based reconstruction. To achieve our goal, we iteratively build multiple, but sparse linear models. Each linear model(More)