Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.

SCI Publications

2005


F. Calderero, A. Ghodrati, D.H. Brooks, G. Tadmor, R.S. MacLeod. “A Method to Reconstruct Activation Wavefronts Without Isotropy Assumptions Using a Level Sets Approach,” In Functional Imaging and Modeling of the Heart: Third International Workshop (FIMH 2005), Barcelona, June 2-4, pp. 195. 2005.



S.P. Callahan, J.L.D. Comba, P. Shirley, C.T. Silva. “Interactive Rendering of Large Unstructured Grids Using Dynamic Level-of-Detail,” In Proceeding of IEEE Visualization 2005, pp. 26. 2005.



S.P. Callahan. “The k-Buffer and its Applications to Volume Rendering,” Note: Masters Thesis, School of Computing, University of Utah, 2005.



I. Corouge, P.T. Fletcher, S. Joshi, J.H. Gilmore, G. Gerig. “Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis,” In Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv, Vol. 8 (Pt. 1), pp. 131--139. 2005.



M.S. Dalton, B.J. Ellis, T.J. Lujan, J.A. Weiss. “MCL Insertion Site and Contact Forces in the ACL-Deficient Knee,” In Proceedings, 51th Annual Orthopaedic Research Society Meeting, Vol. 30, pp. 814. 2005.



R.E. Debski, J.A. Weiss, W.J. Newman, S.M. Moore, P.J. McMahon. “Stress and Strain in the Anterior Band of the Inferior Glenohumeral Ligament During a Simulated Clinical Examination,” In Journal of Shoulder and Elbow Surgery, Vol. 14, pp. 24S--31S. 2005.



D.E. DeMarle, C.P. Gribble, S. Boulos, S.G. Parker. “Memory Sharing for Interactive Ray Tracing on Clusters,” In Parallel Computing, Vol. 31, No. 2, pp. 221--242. 2005.



P. Fife, T. Wei, J.C. Klewicki, P.A. McMurtry. “Stress Gradient Balance Layers and Scale Hierarchies in Wall-Bounded Flows,” In Journal of Fluid Mechanics, Vol. 532, pp. 165--189. June, 2005.
DOI: 10.1017/S0022112005003988

ABSTRACT

Steady Couette and pressure-driven turbulent channel flows have large regions in which the gradients of the viscous and Reynolds stresses are approximately in balance (stress gradient balance regions). In the case of Couette flow, this region occupies the entire channel. Moreover, the relevant features of pressure-driven channel flow throughout the channel can be obtained from those of Couette flow by a simple transformation. It is shown that stress gradient balance regions are characterized by an intrinsic hierarchy of ‘scaling layers’ (analogous to the inner and outer domains), filling out the stress gradient balance region except for locations near the wall. The spatial extent of each scaling layer is found asymptotically to be proportional to its distance from the wall.

There is a rigorous connection between the scaling hierarchy and the mean velocity profile. This connection is through a certain function A(y+) defined in terms of the hierarchy, which remains O(1) for all y+. The mean velocity satisfies an exact logarithmic growth law in an interval of the hierarchy if and only if A is constant. Although A is generally not constant in any such interval, it is arguably almost constant under certain circumstances in some regions. These results are obtained completely independently of classical inner/outer/overlap scaling arguments, which require more restrictive assumptions.

The possible physical implications of these theoretical results are discussed.



M. Foskey, B. Davis, L. Goyal, S. Chang, E. Chaney, N. Strehl, S. Tomei, J. Rosenman, S. Joshi. “Large Deformation Three-Dimensional Image Registration in Image-Guided Radiation Therapy,” In Phys Med Biol, Vol. 50, No. 24, pp. 5869--5892. December 21, 2005.



N. Fout, H. Akiba, K-L. Ma, A.E. Lefohn, J.M. Kniss. “High-Quality Rendering of Compressed Volume Data Formats,” In Proceedings of The Joint EUROGRAPHICS-IEEE VGTC Symposium on Visualization 2005, 2005.



S.E. Geneser, S. Choe, R.M. Kirby, R.S. MacLeod. “Influence of Stochastic Organ Conductivity in 2D ECG Forward Modeling: A Stochastic Finite Element Study,” In Proceedings of The Joint Meeting of The 5th International Conference on Bioelectromagnetism and The 5th International Symposium on Noninvasive Functional Source Imaging within the Human Brain and Heart, pp. 5528--5531. 2005.



A. Ghodrati, D.H. Brooks, G. Tadmor, B.B. Punske, R.S. MacLeod. “Wavefront-based Inverse Electrocardiography using an Evolving Curve State Vector and Phenomenological Propagation and Potential Models,” In IJBEM, Vol. 7, No. 2, pp. 210--213. 2005.



C.E. Goodyer, M. Berzins. “Parallelisation and Scalability Issues in a Multilevel EHL Solver,” Report, No. 2005.05, School of Computing, University of Leeds, 2005.



L. Grady, T. Tasdizen. “A Geometric Multigrid Approach to Solving the 2D Inhomogeneous Laplace Equation with Internal Dirichlet Boundary Conditions,” In IEEE International Conference on Image Processing, Vol. 2, pp. 642--645. September, 2005.



C. Guerra, V. Pascucci. “Line-Based Object Recognition Using Hausdorff Distance: From Range Images to Molecular Secondary Structure,” In Image and Vision Computing, Vol. 23, No. 4, Note: UCRL-JRNL-208551, pp. 405-415. April, 2005.



J.E. Guilkey, J.B. Hoying JB, J.A. Weiss. “Computational modeling of multicellular constructs with the Material Point Method,” In Journal of Biomechanics, pp. (published online). June, 2005.



D. Gullmar, J.R. Reichenbach, A. Anwander, T. Knosche, C.H. Wolters, M. Eiselt, J. Haueisen. “Influence of Anisotropic Conductivity of the White Matter Tissue on EEG Source Reconstruction - An FEM Simulation Study,” In Int. J. Bioelectromag., Vol. 7, No. 1, pp. 108--110. 2005.



H. Guo, A. Rangarajan, S. Joshi. “3-D Diffeomorphic Shape Registration on Hippocampal Data Sets,” In Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv, Vol. 8 (Pt. 2), pp. 984--991. 2005.



A. Gyulassy, V. Natarajan, V. Pascucci, P.-T. Bremer, B. Hamann. “Topology-based Simplification for Feature Extraction from 3D Scalar Fields,” In Proceedings of the IEEE Conference on Visualization (VIS-05), pp. 275--280. October, 2005.



C.W. Hamman, R.M. Kirby, M. Berzins. “Parallelization and Scalability of a Spectral Element Solver,” SCI Institute Technical Report, No. UUSCI-2005-011, University of Utah, 2005.