Abstract Volume data these days is usually massive in terms of its topology, multiple fields, or temporal component. With the gap between compute and memory performance widening, the memory subsystem becomes the primary bottleneck for scientific volume visualization. Simple, structured, regular representations are often infeasible because the buses and interconnects involved need to accommodate the data required for interactive rendering. In this state‐of‐the‐art report, we review works focusing on large‐scale volume rendering beyond those typical structured and regular grid representations. We focus primarily on hierarchical and adaptive mesh refinement representations, unstructured meshes, and compressed representations that gained recent popularity. We review works that approach this kind of data using strategies such as out‐of‐core rendering, massive parallelism, and other strategies to cope with the sheer size of the ever‐increasing volume of data produced by today's supercomputers and acquisition devices. We emphasize the data management side of large‐scale volume rendering systems and also include a review of tools that support the various volume data types discussed.

A statistical multi-lobe approach was recently introduced in order to efficiently handle layered materials rendering as an alternative to expensive general-purpose approaches. However, this approach poorly supports scattering volumes as the method does not account for back-scattering and resorts to single scattering approximations. In this paper, we address these limitations with an efficient solution based upon a transfer matrix approach which leverages the properties of the Henyey-Greenstein phase function. Under this formalism, each scattering component of the stack is described through a lightweight matrix, layering operations are reduced to simple matrix products and the statistics of each BSDF lobe accounting for multiple scattering effects are obtained through matrix operators. Based on this representation, we leverage the versatility of the transfer matrix approach to efficiently handle forward and backward scattering which occurs in arbitrary layered materials. The resulting model enables the reproduction of a wide range of layered structures embedding scattering volumes of arbitrary depth, in constant computation time and with low variance.

In a wide range of scientific fields, 3D datasets production capabilities have widely evolved in recent years, especially with the rapid increase in their sizes. As a result, many large-scale applications, including visualization or processing, have become challenging to address. A solution to this issue lies in providing out-of-core algorithms specifically designed to handle datasets significantly larger than memory. In this article, we present a new approach that extends the broad interactive addressing principles already established in the field of out-of-core volume rendering on GPUs to allow on-demand processing during the visualization stage. We propose a pipeline designed to manage data as regular 3D grids regardless of the underlying application. It relies on a caching approach with a virtual memory addressing system coupled to an efficient parallel management on GPU to provide efficient access to data in interactive time. It allows any visualization or processing application to leverage the flexibility of its structure by managing multi-modality datasets. Furthermore, we show that our system delivers good performance on a single standard PC with low memory budget on the GPU.

Large scale images allow pathologists to perform reviews, using computer workstations instead of microscopes. This trend raises a wide range of issues related to the management of these massive datasets. In particular, efficient solutions for data storage and processing have to be developed in order to deliver increasingly reliable and faster analyses. In addition, the improvement of workflows also requires the reinforcement of visualization capabilities. In this paper, we present a new virtual microscopy (VM) approach for interactive-time navigation in large images stack with 3D visualization on multi-stereo display. Our work is based on a tool that combines 3D pyramidal representation and out-of-core data management for interactive on-demand streaming of large datasets on GPUs. The preliminary results suggest that the proposed solution facilitates the reading and the understanding of data essentially because they are spatialized.

Visualization pipelines and scene graphs are widely used paradigms in rendering applications, the former as a key concept in scientific visualization while the latter provides a powerful representation for 3D scenes in graphics applications. Despite an apparent disparity in usage, they show structural similarities by both using a graph-based architecture. Nevertheless, few attempts have been made to integrate both visualization pipelines and scene graphs in a unified design. This paper presents an architecture based on an extended dataflow network which allows implicit invocation of callbacks on network events. Events are then handled by programmable layers on top of the "dataflow layer" to dynamically build scene graph structures and define a multiparadigm model interface, which forms what we call an "indexed dataflow network". We show an implementation of our architecture using NVIDIA SceniX scene management engine and Qt's model/view framework.

ABSTRACT We attempt to model and visualize the main characteristics of cracks produced on the surface of a desiccating crusted soil: their patterns, their different widths and depths and their dynamics of creation and evolution. In this purpose we propose a method to dynamically produce three‐dimensional (3D) quasi‐static fractures, which takes into account the characteristics of the soil. The main originality of this method is the use of a 3D discrete propagation of ‘shrinkage volumes’ with respect to 2D precalculated paths. In order to get realistic cracks, we newly propose to take into account a possibly inhomogeneous thickness of the shrinking layer by using a watershed transformation to compute these paths. Moreover, we use the waterfall algorithm in order to introduce in our simulation a hierarchy notion in the cracks appearance, which is therefore linked with the initial structure of the surface. In this paper, this method is presented in detail and a validation of the cracks patterns by a comparison with real ones is given.

This paper presents a new algorithm of volume rendering based on a dual representation of data. The algorithm improves both the image generation speed and its quality. Two shape descriptors are used to characterize the object: a Euclidean distance transform (EDT) and a digital Euclidean skeleton. The EDT is used at one point in time to accelerate the image generation and compute the skeleton of the shape, whilst the skeleton is used as an initialization of the processing of the implicit surface. The goal is to build an interactive system of visualization for the analysis of volumetric data, either in the setting of a qualitative exploration or as a guide for qualitative measurements. The speed of treatment together with good visualization should give the feasibility to achieve a 3D survey of a natural object in an interactive manner. The method has been successfully applied to both synthetic and real data. Copyright © 2000 John Wiley & Sons, Ltd.

Morphing is one of the most well-used techniques for producing intermediate images which fill the gap between two stages of a displayed data set. Several 3D morphing methods have been developed for interpolating between synthetic data sets, but none have yet been devised for interpolating between scientific data sets. One of the morphing techniques used for such data sets in 2D is the segment warping algorithm. In this paper, we show that this technique can be extended to 3D data sets. The 3D morphing technique, which is composed of three modules (tweening, warping and dissolving) is first described and then applied to digital volumes (chromosomes at different stages of the cell mitosis) recorded by confocal microscopy. From the intermediate digital volumes created by this technique, movies are produced, which can help in the understanding of the dynamical behaviour of the 3D structure.