Traditional Posters: Diffusion & Perfusion - ismrm

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uncertainty in the large 3D regions defined by FT. Therefore, we will illustrate the appropriate implementation of RB to obtain the uncertainty of fiber tracking parameters (FTPs) such as number of streamlines (NOS). We validated our method with a Monte Carlo simulation showing that RB accurately estimated the SE of the NOS. 1669. Quantitative Improvement of Diffusion Spectrum Imaging Tractography Using Statistical Denoising Li-Wei Kuo 1 , Justin P. Haldar 2 , Yu-Chun Lo 3 , Cheng-Liang Liu 1 , Zhi-Pei Liang 2 , Wen- Yih Isaac Tseng 1,4 1 Center for Optoelectronic Biomedicine, National Taiwan University College of Medicine, Taipei, Taiwan; 2 Department of Electrical and Computer Engineering, Beckman Institute, University of Illinois at Urbana- Champaign, Urbana, IL, United States; 3 Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan; 4 Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan Noise contamination is a significant problem in diffusion spectrum imaging (DSI) tractography, and previous work has proposed a statistical denoising algorithm to mitigate the effects of low signal-to-noise ratio. In this work, improvements to fiber orientation accuracy due to denoising were quantified using a systematic analysis of angular precision and dispersion metrics. Results show that the proposed denoising method significantly improves angular precision and dispersion. Furthermore, the tractography results demonstrate better reconstruction of white-matter structures using the denoised data. Future work will use the proposed denoising algorithm to improve spatial resolution and reduce scan time. 1670. Improved Probabilistic Streamlines Tractography by 2 nd Order Integration Over Fibre Orientation Distributions J-Donald Tournier 1,2 , Fernando Calamante 1,2 , Alan Connelly 1,2 1 Brain Research Institute, Florey Neuroscience Institutes (Austin), Melbourne, Victoria, Australia; 2 Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia Probabilistic streamlines algorithms are amongst the most promising methods for fibre-tracking, but are potentially subject to a number of deficiencies. These include a tendency to overshoot in highly curved regions, and to switch directions in crossing fibre regions. To address both of these issues, we propose a higher-order probabilistic streamlines algorithm, based on 2 nd order integration over fibre orientation distributions (iFOD2), with a computational complexity similar to current first order methods. We demonstrate the advantages of the proposed iFOD2 algorithm on simulated data, and apply the method to in-vivo data. 1671. Tract-Based Parameterization of Local White Matter Geometry Peter Savadjiev 1 , Marek Kubicki 1 , Sylvain Bouix 1 , Gordon L. Kindlmann 2 , Martha E. Shenton 1,3 , Carl-Fredrik Westin 4 1 Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; 2 Computer Science, University of Chicago, Chicago, IL, United States; 3 Psychiatry, VA Boston Healthcare System, , Brockton , MA, United States; 4 Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States Knowledge of fibre geometry and its variation along fibre tracts can be useful for the study of normal and pathological white matter. In this work we present a tract-based analysis of two recently introduced measures of fibre geometry, which compute fibre dispersion and fibre curving, directly from a diffusion tensor field and its gradient. These measures of fibre geometry are mapped and analysed along a parametric representation of fibre tracts. Such representations of fibre tract geometry are an important tool for the understanding of white matter structure. 1672. Towards Image-Dependent Safety Hulls for Fiber Tracking Sebastiano Barbieri 1 , Jan Klein 1 , Christopher Nimsky 2 , Horst K. Hahn 1 1 Fraunhofer MEVIS - Institute for Medical Image Computing, Bremen, Germany; 2 Department of Neurosurgery, University Marburg, Marburg, Germany We make use of a DTI software model in order to systematically analyze the influence of noise, fiber bundle diameter, number of seed points and tensor anisotropy on the magnitude of fiber tracking errors. In our model we simulate image noise and partial volume artifacts. As a measure for fiber tracking errors we introduce a so called "safety radius". The safety radius is used to construct safety hulls, which are tubes that surround the tracked fibers and indicate their margin of error. We further analyze how fibers are spatially distributed inside a cylindrical fiber bundle during the tracking process. 1673. Atlas-Guided Automated Tract Reconstruction of the White Matter Anatomy Yajing Zhang 1 , Kenichi Oishi 2 , Michael I. Miller 3 , Jiangyang Zhang 4 , Susumu Mori 2,5 1 Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States; 2 Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States; 3 Center for Imaging Science, Johns Hopkins University, Baltimore, MD, United States; 4 Radiology and Radiological Science, , Johns Hopkins University School of Medicine, Baltimore, MD, United States; 5 F.M.Kirby Resarch Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States We performed comprehensive studies of human white matter anatomy using a novel atlas based automated fiber tracking system. 130 3-D ROIs were transformed from our brain atlas to the individual subject using non-linear transformations and used for automated fiber tracking. This approach allows exhaustive search of white matter bundles that consistently exist in the normal population. The method was validated by comparing to manual results by experts. We identified 29 short cortico-cortical association fibers in addition
to well-defined major bundles. Probabilistic maps of such tracts in normalized space were constructed for the first time in the normal population. 1674. Global Fiber Tracking Becomes Practical Marco Reisert 1 , Irina Mader 2 , Constantin Anastasopoulus 2 , Susanne Schnell 1 , Valerij Kiselev 1 1 Medical Physics, University Hospital Freiburg, Freiburg, Baden-Wuerttemberg, Germany; 2 Section of Neuroradiology, University Hospital Freiburg Local fiber tracking approaches are based on the 'walker' principle, the fibres are reconstructed path-by-path by small successive steps along the tracts. On the other hand global ideas try to reconstruct all fibres at once by optimizing a certain global objective. Local algorithms are fast but suffer from accumulated errors. Global methods have a more sound foundation but are very complex to optimize. This abstract presents an approach, which fuses both ideas while keeping their advantages. The experiments show that the approach is orders of magnitude faster than recent global approaches while improving the detection performance. 1675. Probabilistic Connectivity in Fibre Tractography Parya MomayyezSiahkal 1 , Kaleem Siddiqi 1 1 School of Computer Science, Centre for Intelligent Machines, McGill University, Montréal, Quebec, Canada We introduce a probabilistic connectivity index between two regions, based on diffusion MRI, by using a stochastic nonlinear differential equation to model the Brownian motion of water molecules in a medium. The model is linked to the physical basis of the diffusion process and leads to promising results on the MICCAI 2008 Fibre cup phantom. Our experiments yield highly curving fibre tracts without the need to impose thresholds on curvature or torsion or to eliminate false positives. An additional benefit is the algorithm's low computational complexity and the fact that its parameters are data-driven and are selected automatically. 1676. Analysis of Connectivity of Gray Matter Regions Using DTI and Graph Theory Amy Kuceyeski 1 , Ashish Raj 1 1 Radiology, Weill Cornell Medical College, New York, NY, United States The connectivity of gray matter regions in the brain via white matter tracts has recently become an area of wide interest due to the advances in imaging techniques that measure structural connections via white matter (DTI. The information that can be extracted from this modality has not yet been harvested fully due to its relative novelty; however some studies have proven its potential. We propose a computational methodology that utilizes DTI and structural images of the brain, graph theory, and clustering algorithms to explore regions of high connectivity and importance to overall connectivity in normal brains. 1677. Fiber Tracking of Human Brain Using Moment-Based Orientation Distribution Function and Multi-Shelled Q-Ball Imaging Eizou Umezawa 1 , Yoshifumi Kuwayama 2 , Akihito Yamamoto 2 , Hikaru Masumoto 2 , Takashi Fukuba 2 , Masao Ohashi 2 , Keiko Terada 2 , Toshiaki Mori 2 , Yutaka Kinomura 2 , Kojiro Yamaguchi 1 , Masayuki Yamada 1 , Hirofumi Anno 1 , Kazuhiro Katada 3 1 School of Health Sciences, Fujita Health University, Toyoake, Aichi, Japan; 2 Radiological Division, Fujita Health University Hospital, Toyoake, Aichi, Japan; 3 Department of Radiology, School of Medicine, Fujita Health University, Toyoake, Aichi, Japan Multi-Shelled QBI (MS-QBI) gives a new orientation distribution function based on the moment of the probability density function. We perform the fiber tracking of human brain based on MS-QBI and confirm the practicability of the method. We implement a simple procedure for streamline fiber trackings of pathways that encounter crossings. The pyramidal tract (PT) can be traced beyond the crossing with the superior longitudinal fasciculus by MS-QBI. The distinction between PT and the corpus callosum in the corona radiata is still difficult. 1678. Effects of Susceptibility Distortion and Phase Encoding Direction on Tract Consistency in Diffusion Tensor Imaging Mustafa Okan Irfanoglu 1,2 , Lindsay Walker 2 , Carlo Pierpaoli 2 1 Department of Radiology, The Ohio State University, Columbus, OH, United States; 2 NICHD, National Institutes of Health, Bethesda, MD, United States The distortions on phase-encoding direction of diffusion weighted images due to magnetic susceptibility and concomitant fields greatly affect the quality and consistency of tractography using on diffusion sequences. In this work, data from a healthy population were acquired in both Right-Left and Anterior-Posterior phase encoding directions and the effects of these distortions and EPI distortion correction were analyzed on specific fiber bundles. Results indicate tracts are greatly affected by these distortions and consistency and quality of the tracts are improved with correction and that this correction process should be part of typical diffusion sequences acquired for tractography purposes. 1679. On the Importance of Appropriate Fibre Population Selection in Diffusion Tractography Jonathan D. Clayden 1 , Chris A. Clark 1 1 Institute of Child Health, University College London, London, Greater London, United Kingdom While a lot of recent research in diffusion MRI has focussed on estimating the orientations of multiple fibre populations within image voxels, little attention has been given to the problem of how to effectively use this information in tractography. Typically a tractography algorithm selects a fibre direction to follow based on continuity, but we show here that a alternative approach based on
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