TRADITIONAL POSTER - ismrm

Poster Sessions
1690. An Accelerated, Alternative Approach for Estimating Zero-Displacement Probability in Hybrid
Diffusion Imaging
A P. Hosseinbor 1 , J O. Fleming 2 , Y-C Wu 3 , A A. Samsonov 4 , A L. Alexander
1 Medical Physics, University of Wisconsin-Madison, Madison, WI, United States; 2 Neurology, University of Wisconsin-Madison;
3 Dartmouth College; 4 Radiology, University of Wisconsin-Madison
In HYDI, Po is conventionally estimated by using signal measurements in all shells (Poall), which requires long scan time. However, the highest diffusionweighting
measurements are likely to contribute most heavily to restricted diffusion (RD) signal. Thus, an alternative, faster approach for characterizing RD
would be to use signal measurements only in outermost shell (Poouter). In this work, we compare both Poall and Poouter approaches in NAWM from MS
patients and WM in a control group. We show that both approaches yield similar statistical properties for characterizing RD, which suggests Poouter is both
adequate and faster than using full q-space measurements.
1691. Combined DTI/HARDI Visualization
Vesna Prckovska 1 , Tim H.J.M. Peeters 1 , Markus van Almsick 1 , Anna Vilanova 1 , Bart ter Haar Romeny 1
1 Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
We present a novel visualization framework that unifies the models from DTI and HARDI, using a classification scheme for model selection. The data is
represented by diffusion tensors or fibers in the Gaussian and HARDI glyphs in the non-Gaussian areas. We exploit the capabilities of modern GPU to
optimize the rendering performance and visual quality of the glyphs. All of the visualization parameters are controlled by the user in real time. Different
color coding on the glyphs enhance the anisotropy information or highlight maxima. This is the first attempt to give fast and intuitive insight into the
complex HARDI data.
1692. Determination of Local Fibre Configuration Using Bayesian Neighbourhood Tract Modeling
Thomas Glyn Close 1,2 , Jacques-Donald Tournier 1,3 , Fernando Calamante 1,3 , Leigh A. Johnston 2,4 , Iven
Mareels 2 , Alan Connelly 1,3
1 Brain Research Institute, Florey Neuroscience Institutes (Austin), Melbourne, Victoria, Australia; 2 School of Engineering and NICTA
VRL, University of Melbourne, Melbourne, Victoria, Australia; 3 Department of Medicine, University of Melbourne, Melbourne,
Victoria, Australia; 4 Howard Florey Insitute, Florey Neuroscience Institutes (Parkville), Melbourne, Victoria, Australia
We present a new method for characterising white matter fibre configurations within local neighbourhoods. Instead of single-voxel based models of fibre
orientations represent the complete tract configuration within a local neighbourhood (eg. 3x3x3 voxels) via a rich tract-segment model. By fitting multiple
tracts simultaneously, this approach utilizes the probability of surrounding tracts to improve the fit of each tract.
1693. Diffusion Gradient Calibration Influences the Accuracy of Fibre Orientation Density Function
Estimation: Validation by Efficiency Measure
Yuliya Kupriyanova 1 , Oleg Posnansky 2 , N. J. Shah 2,3
1 Medical Imaging Physics, Institute of Neuroscience and Medicine - 4, Forschungzentrum Juelich, Juelich, Germany; 2 Medical
Imaging Physics, Institute of Neuroscience and Medicine - 4 , Forschungzentrum Juelich, Juelich, Germany; 3 Department of
Neurology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
Imperfections in the diffusion-weighted (DW) gradients may cause errors in the estimation of diffusion parameters. We present results demonstrating the
influence of these errors in the accuracy of fibre orientation density function (ODF) estimation. A DW gradient calibration scheme, used to mitigate DW
gradient errors, is also described. We compared the reconstructed fibre ODFs from two datasets, acquired in vivo with and without the application of the
calibration scheme and calculated the statistical efficiency of the unbiased fibre ODF estimators for these datasets. It is shown that the calibration procedure
can significantly improve results of the fibre ODF estimation.
1694. Riemannian Median and Its Applications for Orientation Distribution Function Computing
Jian Cheng 1,2 , Aurobrata Ghosh 1 , Tianzi Jiang 2 , Rachid Deriche 1
1 INRIA Sophia Antipolis, Sophia Antipolis, Valbonne, France; 2 Institute of Automation, Chinese Academy of Sciences, Beijing,
China
In this work, we prove the unique existence of the Riemannian median in the space of Orientation Distribution Fuction. Then we explore its two potential
applications, median filtering and atlas estimation.
1695. Impact of Outliers in DTI and Q-Ball Imaging - Clinical Implications and Correction Strategies
Michael Andrew Sharman 1 , Julien Cohen-Adad 2 , Maxime Descoteaux 3 , Arnaud Messé 4,5 , Habib Benali 4,5 ,
Stéphane Lehericy 6,7
1 UMR-S975, CRICM-UPMC/Inserm, Paris, Île-de-France, France; 2 Athinoula A. Martinos Center for Biomedical Imaging,
Massachusetts General Hospital, Harvard Medical School, United States; 3 Department of Computer Science, Sherbrooke University,
Québec, Canada; 4 UMR-S678, UPMC/Inserm, Paris, France; 5 IFR49, Paris, France; 6 Centre for NeuroImaging Research (CENIR),
Hospital Pitié-Salpêtrière , Paris, France; 7 UMR-S975, CRICM-UPMC/Inserm, Paris, France
Corrupted images within acquired diffusion weighted MRI data can have an impact on the estimation of the tensor (in diffusion tensor imaging) and
diffusion ODF (in q-ball imaging). In this study we performed a series of simulations and real data analyses to quantify this impact on derived metrics such
as fractional anisotropy (FA) and generalised FA. From the results of these invetigations, we propose processing strategies to detect and correct corruption
artifacts arising from large, unpredicatable signal variations.