SCIENTIFIC COMPUTING AND IMAGING INSTITUTE
at the University of Utah

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

SCI Publications

2008


J. Cates, P.T. Fletcher, M. Styner, H. Hazlett, R.T. Whitaker. “Particle-Based Shape Analysis of Multi-Object Complexes,” In Proceedings of the 11th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI '08), Lecture Notes In Computer Science (LCNS), pp. 477--485. 2008.
ISBN: 978-3-540-85987-1


A.N.M. Imroz Choudhury, K. Potter, S.G. Parker. “Interactive Visualization for Memory Reference Traces,” In Computer Graphics Forum, In Proceedings of EuroVis 2008, Vol. 27, No. 3, pp. 815--822. May, 2008.


J.D. Daniels, T. Ochotta, L. Ha, C.T. Silva. “Spline-Based Feature Curves from Point-Sampled Geometry,” In The Visual Computer, Vol. 24, No. 6, pp. 449--462. 2008.


J.D. Daniels, C.T. Silva, J. Shepherd, E. Cohen. “Quadrilateral Mesh Simplification,” In ACM Transactions on Graphics - Proceedings of ACM SIGGRAPH Asia 2008, Vol. 27, No. 5, 2008.
DOI: 10.1145/1409060.1409101


S.B. Davidson, J. Freire. “Provenance and Scientific Workflows: Challenges and Opportunities,” In Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 1345--1350. 2008.
ISBN: 978-1-60558-102-6


C. Dietrich, J. Comba, L. Nedel, C.E. Scheidegger, C.T. Silva. “Edge Groups: A New Approach to Understanding the Mesh Quality of Marching Methods,” In IEEE Transactions on Visualization and Computer Graphics (Proceedings of IEEE Visualization 2008), Vol. 14, No. 6, pp. 1651 - 1666. 2008.
DOI: 10.1109/TVCG.2008.122


G. Draper, R. Riesenfeld. “Who Votes For What? A Visual Query Language for Opinion Data,” In IEEE Transactions on Visualization and Computer Graphics, Vol. 14, No. 6, IEEE, pp. 1197--1204. Nov, 2008.
DOI: 10.1109/tvcg.2008.187


G. Draper, Y. Livnat, R. Riesenfeld. “A Visual Query Language for Correlation Discovery and Management,” In Proceedings of Visual and Iconic Language Conference (VaIL 2008), pp. 14--23. 2008.


T. Ellkvist, D. Koop, E.W. Anderson, J. Freire, C.T. Silva. “Using Provenance to Support Real-Time Collaborative Design of Workflows,” In Proceedings of the Second International Provenance and Annotation Workshop (IPAW 2008), pp. 266--279. 2008.


T. Ellkvist, D. Koop, J. Freire, C.T. Silva, L. Stromback. “Using Mediation to Achieve Provenance Interoperability,” In Proceedings of the 2008 Fourth IEEE International Conference on eScience, pp. 398--399. 2008.


A. Fedorov, E. Billet, M.W. Prastawa, G. Gerig, A. Radmanesh, S.K. Warfield, R. Kikinis, N. Chrisochoides. “Evaluation of Brain MRI Alignment with the Robust Hausdorff Distance Measures,” In Lecture Notes in Computer Science, Vol. 5358, Springer, pp. 594--603. 2008.
DOI: 10.1007/978-3-540-89639-5_57


P.T. Fletcher, S. Venkatasubramanian, S. Joshi. “Robust Statistics on Riemannian Manifolds via the Geometric Median,” In IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), pp. 1--8. 2008.
DOI: 10.1109/CVPR.2008.4587747


N.L. Foster, A.Y. Wang, T. Tasdizen, P.T. Fletcher, J.M. Hoffman, R.A. Koeppe. “Realizing the Potential of Positron Emission Tomography with 18F-Fluorodeoxyglucose to Improve the Treatment of Alzheimer,” In Journal of the Alzheimer, Vol. 4, No. 1, Suppl. 1, pp. S29--36. 2008.
PubMed ID: 18631997


N. L. Foster, A.Y. Wang, T. Tasdizen, K. Chen, W. Jagust, R.A. Koeppe, E. Reiman, M.W. Weiner, S. Minoshima. “Cerebral Hypometabolism Suggesting Frototemporal Dementia in an Alzheimer’s Disease Clinical Trial,” In Neurology, Vol. 70, No. 11, pp. A103. 2008.


J. Freire, C.T. Silva. “Towards Enabling Social Analysis of Scientific Data,” In Proceedings of CHI Social Data Analysis Workshop 2008, 2008.

ABSTRACT

Computing has been an enormous accelerator to science and it has led to an information explosion in many different fields. Future advances in science depend on the ability to comprehend these vast amounts of data. In this paper, we discuss challenges and opportunities for social data analysis in the scientific domain.


J. Freire, D. Koop, C.T. Silva. “Provenance for Computational Tasks: A Survey,” In Computing in Science and Engineering, Vol. 10, No. 3, pp. 11--21. 2008.


M. Fuchs, S. Gerber. “Variational Shape Detection in Microscope Images Based on Joint Shape and Image Feature Statistics,” In Proceedings of the IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA 2008), pp. 1--8. 2008.
DOI: 10.1109/CVPRW.2008.4563012

ABSTRACT

This paper presents a novel variational formulation incorporating statistical knowledge to detect shapes in images. We propose to train an energy based on joint shape and feature statistics inferred from training data. Variational approaches to shape detection traditionally involve energies consisting of a feature term and a regularization term. The feature term forces the detected object to be optimal with respect to image properties such as contrast, pattern or edges whereas the regularization term stabilizes the shape of the object. Our trained energy does not rely on these two separate terms, hence avoids the non-trivial task of balancing them properly. This enables us to incorporate more complex image features while still relying on a moderate number of training samples. Cell detection in microscope images illustrates the capability of the proposed method to automatically adapt itself to different image features. We also introduce a nonlinear energy and exemplarily compare it to the linear approach.


W. Gao, Y. Chen, G. Gerig, J.K. Smith, V. Jewells, J.H. Gilmore, W. Lin. “Temporal and Spatial Development of Axonal Maturation and Myelination of White Matter in the Developing Brain,” In American Journal of Neuroradiology, pp. (published online). Nov 11, 2008.
DOI: 10.3174/ajnr.A1363


S.E. Geneser, R.M. Kirby, R.S. MacLeod. “Application of Stochastic Finite Element Methods to Study the Sensitivity of ECG Forward Modeling to Organ Conductivity,” In IEEE Transations on Biomedical Engineering, Vol. 55, No. 1, pp. 31--40. January, 2008.


J.H. Gilmore, L. Smith, H. Wolfe, B. Hertzberg, J.K. Smith, N. Chescheir, D. Evans, C. Kang, R.M. Hamer, W. Lin, G. Gerig. “Prenatal Mild Ventriculomegaly Predicts Abnormal Development of the Neonatal Brain,” In Biological Psychiatry, Vol. 64, No. 12, pp. 1069-1076. Dec, 2008.
PubMed ID: 18835482