Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Monthly Notices is one of the three largest general primary astronomical research publications. It is an international journal, published by the Royal Astronomical Society. This article 1 describes its publication policy and practice.

Monthly Notices of the Royal Astronomical Society

Initial-value ordinary differential equation solution via variable order Adams method (SIVA/DIVA) package is collection of subroutines for solution of nonstiff ordinary differential equations. There are versions for single-precision and double-precision arithmetic. Requires fewer evaluations of derivatives than other variable-order Adams predictor/ corrector methods. Option for direct integration of second-order equations makes integration of trajectory problems significantly more efficient. Written in FORTRAN 77.

Solving Ordinary Differential Equations

Computational geometry

We present a sketching interface for quickly and easily designing freeform models such as stuffed animals and other rotund objects. The user draws several 2D freeform strokes interactively on the screen and the system automatically constructs plausible 3D polygonal surfaces. Our system supports several modeling operations, including the operation to construct a 3D polygonal surface from a 2D silhouette drawn by the user: it inflates the region surrounded by the silhouette making wide areas fat, and narrow areas thin. Teddy, our prototype system, is implemented as a Java™ program, and the mesh construction is done in real-time on a standard PC. Our informal user study showed that a first-time user typically masters the operations within 10 minutes, and can construct interesting 3D models within minutes.

/pdf/teddy-a-sketching-interface-for-3d-freeform-design-qlbvzvgvwj.pdf

Teddy: a sketching interface for 3D freeform design

The focus of this article is on how one group of researchersthe DOE SciDAC Visualization and Analytics Center for EnablingTechnologies (VACET) is tackling the daunting task of enabling knowledgediscovery through visualization and analytics on some of the world slargest and most complex datasets and on some of the world's largestcomputational platforms. As a Center for Enabling Technology, VACET smission is the creation of usable, production-quality visualization andknowledge discovery software infrastructure that runs on large, parallelcomputer systems at DOE's Open Computing facilities and that providessolutions to challenging visual data exploration and knowledge discoveryneeds of modern science, particularly the DOE sciencecommunity.

/pdf/doe-s-scidac-visualization-and-analytics-center-for-enabling-41uj5r7s28.pdf

DOE’s SciDAC Visualization and Analytics Center for Enabling Technologies - Strategy for Petascale Visual Data Analysis Success

We present a method that maps a complex surface geometry to an equally complicated, similar surface. One main objective of our effort is to develop technology for automatically transferring surface annotations from an atlas brain to a subject brain. While macroscopic regions of brain surfaces often correspond, the detailed surface geometry of corresponding areas can vary greatly. We have developed a method that simplifies a subject brain's surface forming an abstract yet spatially descriptive point cloud representation, which we can match to the abstract point cloud representation of the atlas brain using an approach that iteratively improves the correspondence of points. The generation of the point cloud from the original surface is based on surface smoothing, surface simplification, surface classification with respect to curvature estimates, and clustering of uniformly classified regions. Segment mapping is based on spatial partitioning, principal component analysis, rigid affine transformation, and warping based on the thin-plate spline (TPS) method. The result is a mapping between 
topological components of the input surfaces allowing for transfer of annotations.

/pdf/automatic-feature-based-surface-mapping-for-brain-cortices-3zn9n0at3a.pdf

Automatic feature-based surface mapping for brain cortices

Welcome to SCCG 2003! These are the proceedings of the 19th Spring Conference on Computer Graphics held in Budmerice Castle, Slovakia on April 24-27, 2003. As we move into our new millennium, we find that the areas represented by the field of computer graphics now have permeated almost all facets of human endeavors. In the fields of science, engineering, medicine, and entertainment, the impacts of the computer graphics field is influencing the very quality of our lives. The field of computer graphics has grown over the past 19 years, and so has the scope of this conference. This year the conference provides a stimulating program of papers and invited talks on topics that range from virtual reality to rendering.Historically, this SCCG has been the most important conference series in Central Europe. This year, the conference attracted a record number of papers, of which 30 peer-reviewed papers and five invited papers were selected to be presented and appear in these proceedings. The accepted papers covered a wide range of areas in the computer graphics field:• Modeling,• Visualization,• Rendering,• Animation,• Virtual Reality,• Image Processing,• Computational Geometry, and• Multiresolution Methods.Invited papers were given by Professor Hans Hagen, University of Kaiserslautern, Germany, Professor Leif Kobbelt, University of Aachen, Germany, Professor Franz W. Leberl, University of Technology, Graz, Austria, and Professor Alan Chalmers, Bristol University, UK. This compilation of high-quality research would not have been possible without the hard work and diligence of the authors and speakers, as well as the international program committee who performed the reviews.The general sponsor is HP Invent Slovakia who covers the post-conference publishing of this book by ACM SIGGRAPH. International sponsor for both CESCG 2003 student seminar and our conference is Visegrad Fund and the administrator is Prof. Laszlo Szirmay-Kalos from Budapest. Sponsoring of teachers is kindly provided by DDik, Peter Borovský, Vlado Trgo, Peter Gejgus, Michal Sudolský, Jaro Placek, Jozef Martinka, Silvester Czanner, Jan Ciger and many others. They did, traditionally, an excellent job.

Proceedings of the 19th Spring Conference on Computer Graphics

Large-scale simulations are often performed on machines without the necessary graphics hardware for visualization. Transferring full resolution data to a suitable machine for visualization is impractical and undesirable. We investigate solutions to the remote visualization problem for large-scale Smoothed Particle Hydrodynamics (SPH) simulations. Previous remote visualization strategies for SPH perform rendering on the server side and send rendered images to the client viewer. These approaches suffer from delays due to network latency in sending entire images every frame and adversely affect interactive visual data analysis. WebGL enables hardware acceleration for rendering in the browser. We combine WebGL volume rendering rendering with data compression and intelligent streaming to provide a fast and flexible remote visualization solution for SPH simulations, which enables easier access to simulations for analysis and sharing of data.

WebGL-Enabled Remote Visualization of Smoothed Particle Hydrodynamics Simulations

Feature-based visualization of flow fields has proven as an effective tool for flow analysis. While most flow visualization techniques operate on vector field data, our visualization techniques make use of a different simulation output: Particle Tracers. Our approach solely relies on integral lines that can be easily obtained from most simulation software. The task is the visualization of dense integral line data. We combine existing methods for streamline visualization, i.e. illumination, transparency, and halos, and add ambient occlusion for lines. But, this only solves one part of the problem: because of the high density of lines, visualization has to fight with occlusion, high frequency noise, and overlaps. As a solution we propose non-automated choices of transfer functions on curve properties that help highlighting important flow features like vortices or turbulent areas. These curve properties resemble some of the original flow properties. With the new combination of existing line drawing methods and the addition of ambient occlusion we improve the visualization of lines by adding better shape and depth cues. The intelligent use of transfer functions on curve properties reduces visual clutter and helps focusing on important features while still retaining context, as demonstrated in the examples given in this work.

Kenneth I. Joy

Papers

DOE’s SciDAC Visualization and Analytics Center for Enabling Technologies - Strategy for Petascale Visual Data Analysis Success

Automatic feature-based surface mapping for brain cortices

Proceedings of the 19th Spring Conference on Computer Graphics

WebGL-Enabled Remote Visualization of Smoothed Particle Hydrodynamics Simulations

Feature-based Visualization of Dense Integral Line Data.