Large 3D Datasets Research Articles

Implementation and Complexity of the Watershed-from-Markers Algorithm Computed as a Minimal Cost Forest

The watershed algorithm belongs to classical algorithms in mathematical morphology. Lotufo et al. published a principle of the watershed computation by means of an Image Foresting Transform (IFT), which computes a shortest path forest from given markers. The algorithm itself was described for a 2D case (image) without a detailed discussion of its computation and memory demands for real datasets. As IFT cleverly solves the problem of plateaus and as it gives precise results when thin objects have to be segmented, it is obvious to use this algorithm for 3D datasets taking in mind the minimizing of a higher memory consumption for the 3D case without loosing low asymptotical time complexity of O(m+C) (and also the real computation speed). The main goal of this paper is an implementation of the IFT algorithm with a priority queue with buckets and careful tuning of this implementation to reach as minimal memory consumption as possible. The paper presents five possible modifications and methods of implementation of the IFT algorithm. All presented implementations keep the time complexity of the standard priority queue with buckets but the best one minimizes the costly memory allocation and needs only 19-45% of memory for typical 3D medical imaging datasets. Memory saving was reached by an IFT algorithm simplification, which stores more elements in temporary structures but these elements are simpler and thus need less memory. The best presented modification allows segmentation of large 3D medical datasets (up to 512x512x680 voxels) with 12-or 16-bits per voxel on currently available PC based workstations.

Rapid prototyping models generated from machine vision data

This paper presents the development of both hardware and software systems suitable for the three-dimensional (3D) digitization and computer modeling of objects intended for manufacture via computer numerically controlled (CNC) machining or rapid prototyping and tooling systems. The hardware sub-system is comprised of a 3D machine vision sensor integrated with a CNC machine tool. The software sub-system is comprised of modules capable of modeling very large 3D data sets (termed cloud data) using a unified, non-redundant triangular mesh. This representation is accomplished from the 3D data points by a novel triangulation process. Several case studies are presented that illustrate the efficacy of the technique for rapid manufacture from an initial designer’s model.

The transfer function bake-off

Direct volume rendering is a key technology for visualizing large 3D data sets from scientific or medical applications. Transfer functions are particularly important to the quality of direct volume-rendered images. A transfer function assigns optical properties, such as color and opacity, to original values of the data set being visualized. Unfortunately, finding good transfer functions proves difficult. It is one of the major problems in volume visualization. The article examines four of the currently most promising approaches to transfer function design. The four approaches are: trial and error, with minimum computer aid; data-centric, with no underlying assumed model; data-centric, using an underlying data model; and image-centric, using organized sampling.

Parameter-Controlled Volume Thinning

The availability of large 3D datasets has made volume thinning essential for compact representation of shapes. The density of the skeletal structure resulting from the thinning process depends on the application. Current thinning techniques do not allow control over the density and can therefore address only specific applications. In this paper, we describe an algorithm which uses a thinness parameter to control the thinning process and thus the density of the skeletal structure. We present applications from CFD and medical visualization and show how the skeletal structure can be used in these domains. We also illustrate a technique for constructing a centerline for surgical navigation.

Offline rendering technique for 3D visualisation in the world wide web

The overall acceptance and easy access to the World Wide Web (WWW) makes it to an interesting media for the exchange of a wide range of research information. But unfortunately there is no fully functional Internet technique available for real interactive 3D visualisation up to now. The basic WWW concept, high net traffic and slow Internet servers prevent the interactive exchange of large 3D-datasets. Techniques which supports offline rendering may become a solution to work around these problems until more satisfying techniques for interactive work in the WWW are available.

Space-time modelling of the Lower Rhine Basin supported by an object-oriented database

Within the framework of the Collaborative Research Centre (CRC, SFB 350) at Bonn University, dealing with interacting geological processes in continental regimes, a joint 3D/4D GIS project is developed by geologists and computer scientists. When analysing and modelling the structural and sedimentary evolution of the Cenozoic intracratonic Lower Rhine Basin in NW Germany, the need emerged to combine methods and tools of space-time modelling of geologically defined geometries with advanced database management techniques. Computer aided geological design typically requires operations for storage and retrieval of large 3D data sets together with their attributes and topological relations and for the generation of model surfaces of stratigraphic boundaries and faults, which in turn define the boundaries of geological bodies developing in time. The requirements of interactive visualisation, analysis and modification of complex and time dependent geometries entail the demand for spatial, topological and time-related database queries as well as for various consistency and integrity tests. Considering these specific geological requirements, an object-oriented geo-database kernel system has been designed and implemented as a “GeoToolKit” for 3D/4D geoscience applications.

PVR: high-performance volume rendering

Traditional volume rendering methods are too slow to provide interactive visualization, especially for large 3D data sets. The PVR (parallel volume rendering) system implements parallel volume rendering techniques that speed up the visualization process. Moreover, it helps computational scientists, engineers, and physicians to more effectively apply volume rendering to visualization tasks. The authors describe the PVR system that they have developed in a collaboration between the State University of New York at Stony Brook and Sandia National Laboratories. PVR is an attempt to provide an easy-to-use portable system for high performance visualization with the speed required for interactivity and steering. The current version of PVR consists of about 25000 lines of C and Tcl/Tk code. It has been used at Stony Brook, Sandia, and Brookhaven National Labs to visualize large data sets for over a year.