SCIENTIFIC COMPUTING AND IMAGING INSTITUTE
at the University of Utah

An internationally recognized leader in visualization, scientific computing, and image analysis

SCI Publications

2000


R.E. Hogan, K.E. Mark, I. Choudhuri, L. Wang, S. Joshi, M.I. Miller, R. Bucholz. “Magnetic Resonance Imaging Deformation-Based Segmentation of the Hippocampus in Patients with Mesial Temporal Sclerosis and Temporal Lobe Epilepsy,” In J Digit Imaging, Vol. 13, No. 2 (Suppl. 1), pp. 217--218. May, 2000.


R.E. Hogan, R.D. Bucholz, I. Choudhuri, K.E. Mark, C.S. Butler, S. Joshi. “Shape-analysis of hippocampal surface structure in patients with unilateral mesial temporal sclerosis,” In Journal of Digital Imaging, Vol. 13, No. 2, pp. 39--42. 2000.


M. Ikits. “Coregistration of Pose Measurement Devices Using Nonlinear Least Squares Parameter Estimation,” School of Computing Technical Report, No. UUCS-00-018, University of Utah, 2000.


C.R. Johnson, S.G. Parker, D. Weinstein. “Large-Scale Computational Science Applications Using the SCIRun Problem Solving Environment,” In Proceedings of The International Supercomputer Conference 2000, 2000.


S. Joshi, M.I. Miller. “Landmark Matching Via Large Deformation Diffeomorphisms,” In IEEE Transactions on Image Processing, Vol. 9, No. 8, pp. 1357--1370. August, 2000.


G.L. Kindlmann, D.M. Weinstein, D. Hart. “Strategies for Direct Volume Rendering of Diffusion Tensor Fields,” In IEEE Trans. Vis & Comp. Graph., Vol. 6, No. 2, pp. 124--138. April-June, 2000.


Y. Livnat, S.G. Parker, C.R. Johnson. “Fast Isosurface Extraction Methods for Large Image Data Sets,” In Handbook of Medical Imaging, Edited by A.N. Bankman, Academic Press, San Diego, CA pp. 731--745. Nov, 2000.


S.G. Parker, M. Miller, C.D. Hansen, C.R. Johnson. “Computational Steering and the SCIRun Integrated Problem Solving Environment,” In Proceedings of Dagstuhl 1997 Workshop on Scientific Visualization, Note: Invited and peer reviewed, Edited by Hans Hagen and Greg Nielson and Frits Post, pp. 257--266. 2000.


V. Pascucci, C.L. Bajaj. “Time Critical Isosurface Refinement and Smoothing,” In Proceedings of the ACM/IEEE Volume Visualization and Graphics Symposium 2000, Salt lake City, Utah, Note: UCRL-JC-139628, pp. 33--42. October, 2000.


E. Reinhard, B. Smits, C.D. Hansen. “Dynamic Acceleration Structures for Interactive Ray Tracing,” In Proceedings Eurographics Workshop on Rendering, Brno, Czech Republic, pp. 299--306. June, 2000.


E. Reinhard, C.D. Hansen. “A Comparison of Parallel Compositing Techniques on Shared Memory Architectures,” In Proceedings of The 2nd Eurographics Workshop on Parallel Graphics and Visualization, Spain, pp. 115--124. September, 2000.


G. Scheuermann, W. Kollmann, X. Tricoche, T. Wischgoll. “Evolution of Topology in Axi-Symmetric and 3D Viscous Flows,” In Numerical Simulations of Incompressible Flows, World Scientific Publishing, New Jersey, pp. 622--643. 2000.


A. Shamir, V. Pascucci, C.L. Bajaj. “Multi-Resolution Dynamic Meshes with Arbitrary Deformations,” In Proceedings of IEEE Conference on Visualization (VIS-00), Salt lake City, Utah, Note: UCRL-JC-139680, pp. 423--430. 2000.


P. Sutton, C.D. Hansen. “Accelerated Isosurface Extraction in Time-varying Fields,” In IEEE Trans. Vis & Comp. Graph., Vol. 6, No. 2, pp. 98--107. 2000.


P.M. Sutton, C.D. Hansen, H.W. Shen, D. Schikore. “A Case Study of Isosurface Extraction Algorithm Performance,” In Proceeding of The Joint Eurographics - IEEE TCVG Symposium on Visualization 2000, Amsterdam, pp. 259--268. May, 2000.


T. Tasdizen, J.-P. Tarel, D.B. Cooper. “Improving the Stability of Algebraic Curves for Applications,” In IEEE Transactions on Image Processing, Vol. 9, No. 3, pp. 405--416. March, 2000.


T. Tasdizen, D.B. Cooper. “Boundary Estimation from Intensity/Color Images with Algebraic Curve Models,” In Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, IEEE, 2000.
DOI: 10.1109/icpr.2000.905308

ABSTRACT

A concept and algorithm are presented for non-iterative robust estimation of piecewise smooth curves of maximal edge strength in small image windows-typically 8/spl times/8 to 32/spl times/32. This boundary-estimation algorithm has the nice properties that it uses all the data in the window and thus can find locally weak boundaries embedded in noise or texture and boundaries when there are more than two regions to be segmented in a window; it does not require step edges-but handles ramp edges well. The curve-estimates found are among the level sets of a dth degree polynomial fit to "suitable" weightings of the image gradient vector at each pixel in the image window. Since the polynomial fitting is linear least squares, the computation to this point is very fast. Level sets then chosen to be appropriate boundary curves are those having the highest differences in average gray level in regions to either side. This computation is also fast. The boundary curves and segmented regions found are suitable for all purposes but especially for indexing using algebraic curve invariants in this form.


A.S. Tomlin, S. Ghorai, G. Hart, M. Berzins. “3-D Adaptive Unstructured Meshes in Air Pollution Modelling,” In Environmental Modeling and Software, Vol. 15, No. 4, pp. 681--692. 2000.


N. Touheed, P. Selwood, P.K. Jimack, M. Berzins. “A Comparison of Some Dynamic Load Balancing Algorithms for a Parallel Adaptive Flow Solver,” In Parallel Computing, Vol. 26, No. 12, pp. 1535--1554. 2000.


X. Tricoche, G. Scheuermann, H. Hagen. “Higher Order Singularities in Piecewise Linear Vector Fields,” In The Mathematics of Surfaces IX, Springer, London, pp. 99--113. 2000.