SCI Publications

2009


C. Goodlett, P.T. Fletcher, J.H. Gilmore, G. Gerig. “Group Analysis of DTI Fiber Tract Statistics with Application to Neurodevelopment,” In NeuroImage, Vol. 45, pp. S133--S142. December, 2009.
DOI: 10.1016/j.neuroimage.2008.10.060
PubMed ID: 19059345
PubMed Central ID: PMC2727755

ABSTRACT

Diffusion tensor imaging (DTI) provides a unique source of information about the underlying tissue structure of brain white matter in vivo including both the geometry of major fiber bundles as well as quantitative information about tissue properties represented by derived tensor measures. This paper presents a method for statistical comparison of fiber bundle diffusion properties between populations of diffusion tensor images. Unbiased diffeomorphic atlas building is used to compute a normalized coordinate system for populations of diffusion images. The diffeomorphic transformations between each subject and the atlas provide spatial normalization for the comparison of tract statistics. Diffusion properties, such as fractional anisotropy (FA) and tensor norm, along fiber tracts are modeled as multivariate functions of arc length. Hypothesis testing is performed non-parametrically using permutation testing based on the Hotelling T(2) statistic. The linear discriminant embedded in the T(2) metric provides an intuitive, localized interpretation of detected differences. The proposed methodology was tested on two clinical studies of neurodevelopment. In a study of 1 and 2 year old subjects, a significant increase in FA and a correlated decrease in Frobenius norm was found in several tracts. Significant differences in neonates were found in the splenium tract between controls and subjects with isolated mild ventriculomegaly (MVM) demonstrating the potential of this method for clinical studies.


S. Gouttard, M.W. Prastawa, E. Bullitt, W. Lin, C. Goodlett, G. Gerig. “Constrained Data Decomposition and Regression for Analyzing Healthy Aging from Fiber Tract Diffusion Properties,” In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009, Lecture Notes in Computer Science LNCS, Vol. 5761, pp. 321--328. 2009.
PubMed ID: 20426003


J. Guilkey, T. Harman, J. Luitjens, J. Schmidt, J. Thornock, J.D. de St. Germain, S. Shankar, J. Peterson, C. Brownlee. “Uintah User Guide Version 1.1,” SCI Technical Report, No. UUSCI-2009-007, SCI Institute, University of Utah, 2009.


L.K. Ha, J. Krüger, T. Fletcher, S. Joshi, C.T. Silva. “Fast Parallel Unbiased Diffeomorphic Atlas Construction on Multi-Graphics Processing Units,” In Proceedings of the Eurographics Symposium on Parallel Graphics and Visualization 2009, 2009.
DOI: 0.2312/EGPGV/EGPGV09/041-048

ABSTRACT

Unbiased diffeomorphic atlas construction has proven to be a powerful technique for medical image analysis, particularly in brain imaging. The method operates on a large set of images, mapping them all into a common coordinate system, and creating an unbiased common template for studying intra-population variability and interpopulation differences. The technique has also proven effective in tissue and object segmentation via registration of anatomical labels. However, a major barrier to the use of this approach is its high computational cost. Especially with the increasing number of inputs and data size, it becomes impractical even with a fully optimized implementation on CPUs. Fortunately, the highly element-wise independence of the problem makes it well suited for parallel processing. This paper presents an efficient implementation of unbiased diffeomorphic atlas construction on the new parallel processing architecture based on Multi-Graphics Processing Units (Multi-GPUs). Our results show that the GPU implementation gives a substantial performance gain on the order of twenty to sixty times faster than a single CPU and provides an inexpensive alternative to large distributed-memory CPU clusters.


L.K. Ha, J. Krüger, C.T. Silva. “Fast 4-way parallel radix sorting on GPUs,” In Computer Graphic Forum, 2009.

ABSTRACT

Efficient sorting is a key requirement for many computer science algorithms. Acceleration of existing techniques as well as developing new sorting approaches is crucial for many realtime graphics scenarios, database systems, and numerical simulations to name just a few. It is one of the most fundamental operations to organize and filter the ever growing massive amounts of data gathered on a daily basis. While optimal sorting models for serial execution on a single processor exist, efficient parallel sorting remains a challenge. In this paper we present a hardware-optimized parallel implementation of the radix sort algorithm that results in a significant speed up over existing sorting implementations. We outperform all known GPU based sorting systems by about a factor of two and eliminate restrictions on the sorting key space. This makes our algorithm not only the fastest, but also the first general GPU sorting solution.


C.D. Hansen, C.R. Johnson, V. Pascucci, C.T. Silva. “Visualization for Data-Intensive Science,” In The Fourth Paradigm: Data-Intensive Science, Edited by S. Tansley and T. Hey and K. Tolle, Microsoft Research, pp. 153--164. 2009.


H.C. Hazlett, M.D. Poe, A.A. Lightbody, G. Gerig, J.R. MacFall, A.K. Ross, J. Provenzale, A. Martin, A.L. Reiss, J. Piven. “Teasing apart the heterogeneity of autism: Same behavior, different brains in toddlers with fragile X syndrome and autism,” In Journal of Neurodevelopmental Disorders, Vol. 1, No. 1, pp. 81--90. 2009.
PubMed ID: 20700390


H.B. Henninger, S.A. Maas, J.H. Shepherd, S. Joshi, J.A. Weiss. “Transversely Isotropic Distribution of Sulfated Glycosaminoglycans in Human Medial Collateral Ligament: A Quantitative Analysis,” In Journal of Structural Biology, Vol. 165, pp. 176-183. 2009.
PubMed ID: 19126431


H.B. Henninger, S.P. Reese, A.E. Anderson, J.A. Weiss. “Validation of computational models in biomechanics,” In Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, Vol. 224, No. 7, SAGE Publications, pp. 801--812. 2009.


J. Hinkle, P.T. Fletcher, Brian Wang, B. Salter, S. Joshi. “4D MAP image reconstruction incorporating organ motion,” In Information Processing in Medical Imaging, Lecture Notes in Computer Science LNCS, Vol. 5636, pp. 676--687. 2009.
PubMed ID: 19694303


B.M. Isaacson, J.G. Stinstra, R.S. MacLeod, J.B. Webster, J.P. Beck, R.D. Bloebaum. “Bioelectric Analyses of an Osseointegrated Intelligent Implant Design System for Amputees,” In JoVE, Vol. 29, 2009.


W.-K. Jeong, J. Beyer, M. Hadwiger, A. Vazquez, H. Pfister, R.T. Whitaker. “Scalable and Interactive Segmentation and Visualization of Neural Processes in EM Datasets,” In IEEE Transactions on Visualization and Computer Graphics, Proceedings of the 2009 IEEE Visualization Conference, Vol. 15, No. 6, pp. 1505--1514. Sept/Oct, 2009.


E. Jurrus, M. Hardy, T. Tasdizen, P.T. Fletcher, P. Koshevoy, C.-B. Chien, W. Denk, R.T. Whitaker. “Axon Tracking in Serial Block-Face Scanning Electron Microscopy,” In Medical Image Analysis (MEDIA), Vol. 13, No. 1, Elsevier, pp. 180--188. February, 2009.
PubMed ID: 18617436


E. Jurrus, A.R.C. Paiva, S. Watanabe, R.T. Whitaker, E.M. Jorgensen, T. Tasdizen. “Serial Neural Network Classifier for Membrane Detection using a Filter Bank.,” SCI Technical Report, No. UUSCI-2009-006, SCI Institute, University of Utah, 2009.


E. Jurrus, A.R.C. Paiva, S. Watanabe, R. Whitaker, E.M. Jorgensen, T. Tasdizen. “Serial Neural Network Classifier for Membrane Detection using a Filter Bank,” In Proc. Workshop on Microscopic Image Analysis with Applications in Biology, Bethesda, MD, USA, 2009.


A. Knoll, I. Wald, C.D. Hansen. “Coherent Multiresolution Isosurface Ray Tracing,” In The Visual Computer, Vol. 25, No. 3, pp. 209--225. 2009.


A. Knoll, Y. Hijazi, C.D. Hansen, I. Wald, H. Hagen. “Fast Ray Tracing of Arbitrary Implicit Surfaces with Interval and Affine Arithmetic,” In Computer Graphics Forum, Vol. 28, No. 1, pp. 26--40. 2009.


A. Knoll, Y. Hijazi, R. Westerteiger, M. Schott, C.D. Hansen, H. Hagen. “Volume Ray Casting with Peak Finding and Differential Sampling,” In IEEE Transactions on Visualization and Computer Graphics, Proceedings of the 2009 IEEE Visualization Conference, Vol. 15, No. 6, pp. 1571--1578. Sept/Oct, 2009.


A. Knoll, Y. Hijazi, R. Westerteiger, M. Schott, C.D. Hansen, Hans Hagen. “Volume Ray Casting with Peak Finding and Differential Sampling,” In IEEE Transactions on Visualization and Computer Graphics, Vol. 15, No. 6, pp. 1571-1578. 2009.


J. Krüger, T. Fogal. “Focus and Context - Visualization without the Complexity,” In Proceedings of the World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, IFMBE Proceedings, Vol. 25/13, Springer Berlin Heidelberg, pp. 44--48. 2009.