SCI Institute Welcomes New Faculty
Mike Kirby joins us from Brown University.The focus of his research focus deals with large- scale scientific computing and visualization, with an emphasis on the scientific cycle of mathematical modeling, computation, visualization, evaluation, and understanding. His primary research interests are: Computational Science and Engineering, Concurrent Programming, Scientific Visualization, Interdisciplinary Collaboration across Computer Science, Engineering, Applied Math, Computational Steering, and High Performance Computing.Martin Berzins joins us from the University of Leeds where he is also Professor of Scientific Computing, Co-director of the Computational PDEs Unit, and head of the Scientific Computing and Visualization research group. His primary interests are in the fields of Adaptive Numerical Methods and software, Unstructured Tetrahedral Meshes, Reacting Flows, Time Dependent PDEs, Parallel Algorithms, and Computational Fluid and Solid Mechanics Applications.
Visualization of Vortex Flow Structures in Aerodynamics Applications
Computational Fluid Dynamics (CFD) has become an essential tool in various engineering fields. In aeronautics it is a key element in the design of modern aircrafts. The performances of today's computers combined with the increasing complexity of physical models yields numerical simulations that accurately reproduce the flow structures observed in practical experiments and permit to study their impact on flight stability. Yet, to fully exploit the huge amount of information contained in typical data sets engineers require powerful post-processing techniques that allow insight into the results of their large-scale computation.
Flow visualization aims at addressing this challenge by offering intuitive and effective depictions of interesting flow patterns. Unfortunately, many problems remain that limit the usefulness of existing methods in practical applications. Our recent work has focused on the design of new visualization techniques suitable for large-scale CFD simulations. Special emphasis was put on critical flight situations that lead to turbulent and vortical flows as well as complex and structurally involved phenomena like flow recirculation and vortex breakdown.
Visualization of Anatomic Covariance Tensor Fields
The computation, visualization, and interpretation of brain variability remains a significant challenge in computational neuroanatomy. Current deformable registration methods can generate, for each vertex of a polygonal mesh modeling the cortical surface, a distribution of displacement vectors between the individual models and their average, which can be summarized as a covariance tensor. While analysis of anatomical covariance tensor fields promises insight into the structural components of aging and disease, basic understanding of the tensor field structure is hampered by the lack of effective methods to create informative and interactive visualizations. We describe a novel application of superquadric tensor glyphs to anatomic covariance tensor fields, supplemented by colormaps of important tensor attributes. The resulting visualizations support a more detailed characterization of population variability of brain structure than possible with previous methods, while also suggesting directions for subsequent quantitative analysis.
 Figure 1: (a) Ellipsoid tensor glyphs, (b) Space of superquadrics, (c) Superquadric tensor glyphs. Ellipsoidal glyphs (a) suffer from visual ambiguity. The range of superquadrics (b) used for tensor glyphs is highlighted with the gray triangle. Superquadric glyphs (c) differentiate shape and convey orientation more clearly than do ellipsoids. |
Interactive Point Based Isosurface Extraction
We have proposed a novel point-based approach to view dependent isosurface extraction. We also introduce a fast visibility query system for the view dependent traversal, which exhibits moderate memory requirements. Using this technique, we achieved an interactive interrogation of the full visible woman dataset (1GB) at more then four frames per second on a desktop computer. The point-based approach is based on an extraction scheme that classifies different sections of the isosurface into four categories. The classification is based on the size of the geometry when projected onto the screen. In particular, we use points to represent small and sub-pixel triangles, as well as large sections of the isosurface whose projection has sub-pixel size. An important issue raised by point-based processing is how to assign a normal to an isolated point representing a large, but far, section of the isosurface. We propose to define such normals during a post processing of the extracted isosurface and provide the corresponding hardware implementation.
 Figure 1: Left: A section of the visible female skeleton. Middle: A closeup view of the extracted points. Right: The final visibility mask. The color represent different levels of the mask hierarchy |
BioTensor: Visualizing Diffusion Tensor MRI
Diffusion tensor MRI visualization is a growing field of research. The scanners are collecting better data all the time, and doctors and scientists are constantly discovering new applications for this data. However, unlike scalar and vector data, high-dimensional tensors are not always intuitive to visualize. When devising new strategies for DT-MRI visualization, it is important to understand both what exactly it is that is being measured and what insights the doctors and scientists are hoping to gain from the data.The success of diffusion magnetic resonance imaging (MRI) is deeply rooted in the powerful concept that during their random, diffusion-driven displacements, molecules probe tissue structure at a microscopic scale well beyond the usual image resolution. As diffusion is truly a three dimensional process, molecular mobility in tissues may be anisotropic, as in brain white matter. With diffusion tensor imaging (DTI), diffusion anisotropy effects can be fully extracted, characterized, and exploited, providing even more exquisite details on tissue microstructure. The most advanced application is certainly that of fiber tracking in the brain, which, in combination with functional MRI, might open a window on the important issue of connectivity. DTI has also been used to demonstrate subtle abnormalities in a variety of diseases (including stroke, multiple sclerosis, dyslexia, and schizophrenia) and is currently becoming part of many routine clinical protocols.
Scientific Visualization in Small Animal Imaging
Biomedical applications of small animal imaging are creating exciting opportunities to extend the scientific impact of visualization research. Specifically, the effective pairing of non-linear image filtering and direct volume rendering is one strategy for scientists to quickly explore and understand the volumetric scans of their specimens. Microscopic computed tomography imaging is an increasingly popular and powerful modality for small animal imaging. Here we highlight early work from collaborations at the University of Utah between the Scientific Computing and Imaging (SCI) Institute and the Department of Bioengineering, and between the SCI Institute and the Division of Pediatric Hematology-Oncology in the Department of Pediatrics. In the first instance, volume rendering provides information about the three-dimensional configuration of an electrode array implanted into the auditory nerve of a feline. In the second instance, volume rendering shows promise as a tool for visualizing bone tissue in the mouse embryo, although the signal-to-noise characteristics of the data require the use of sophisticated image pre-processing.
The data for both of these investigations was acquired with a General Electric EVS RS-9 computed tomography scanner at the University of Utah Small Animal Imaging Facility. The scanner generates 16-bit volumes roughly one gigabyte in size, with a spatial resolution of 21 x 21 x 21 microns.
Undergraduate Research at the SCI Institute
Collaborative Remote Visualization
Introduction
In the last few years, scientists and researchers have given a great deal of attention to the area of remote visualization of scientific datasets within collaborative environments. This recent interest has been fueled by the use of interactive viewing as the primary means by which researchers explore large datasets. However, researchers often need to extend this interactivity in order to collaborate with colleagues who are geographically separated. Most current remote visualization tools allow multiple parties to view images from different locations, but pose problems with efficiency and user interactivity.First Year ESP Recipients Walk at Graduation
Pictured here are three of our first year scholarship recipients of the Undergraduate Engineering Scholars Program who walked at graduation this May. Darby J Van Uitert, Scott Little, and Rebecca Bott received their degrees from the University of Utah College of Engineering in Computer Science, Electrical Engineering, and Bioengineering respectively.Established in 1999 by Chris Johnson and the College of Engineering, the Engineering Scholars Program is a scholarship opportunity for incoming freshmen interested in aspects of engineering and computer science. The quest of the ESP is to leverage the exciting engineering-based research at the University by exposing the first year students to actual research activities. The addition of a research component to the first year student's experience allows the student to see over the horizon offered by prerequisite courses. By giving the first year student a more in-depth look into engineering we propose to increase the enthusiasm level of the students with the result being significantly improved retention rates. Higher retention rates translate into a larger and better-trained graduating class of much-needed engineers and computer scientists.
These students are the best and brightest with an average GPA of 3.96 and an average ACT score of 31. Now in its fourth year, the number of scholarship recipients has increased from nine in 1999 to fifteen in 2002.
Star-Ray Interactive Ray-Tracer Debuts at SIGGRAPH 2002
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(left to right) Living Room Scene, Graphics Museum, Science Room, Galaxy Room, Atlantis Scene