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White Matter Fiber Tracking Computation Based on Diffusion Tensor Imaging for Clinical Applications

Paulo R. Dellani, Martin Glaser, Paulo R. Wille, Goran Vucurevic, Axel Stadie, Thomas Bauermann, Andrei Tropine, Axel Perneczky, Aldo von Wangenheim, Peter Stoeter
2006 Journal of digital imaging  
Fiber tracking was implemented based on existing line propagation algorithms, but it includes a heuristic for fiber crossings in the case of disk-shaped diffusion tensors.  ...  Fiber tracking allows the in vivo reconstruction of human brain white matter fiber trajectories based on magnetic resonance diffusion tensor imaging (MR-DTI), but its application in the clinical routine  ...  (c) Two ROIs were combined with a Boolean OR operation, and all the trajectories crossing one or the other ROI were selected.  ... 
doi:10.1007/s10278-006-0773-7 pmid:16946990 pmcid:PMC3043892 fatcat:t5yqiyrlkjd7jhq266e4a4pz54

A multiple streamline approach to high angular resolution diffusion tractography

Yi-Ping Chao, Jyh-Horng Chen, Kuan-Hung Cho, Chun-Hung Yeh, Kun-Hsien Chou, Ching-Po Lin
2008 Medical Engineering and Physics  
In human brain, one third of the regions were attributed as one fiber distribution, which might contain more than one fiber orientation [5] .  ...  This approach has non-invasively been demonstrated in the human brain with diffusion tensor tractography.  ...  Acknowledgements The work was supported in part by research grants from National Science Council (NSC-96-2752-H-010-004-PAE) and Taipei City Hospital (TCH-95002-62-071).  ... 
doi:10.1016/j.medengphy.2008.01.010 pmid:18375171 fatcat:6sb4jdwpdnct5b6wn7s2hcb4wy

Information-Theoretic Approach for Automated White Matter Fiber Tracts Reconstruction

Ferran Prados, Imma Boada, Miquel Feixas, Alberto Prats-Galino, Gerard Blasco, Josep Puig, Salvador Pedraza
2012 Neuroinformatics  
Fiber tracking is the most popular technique for creating white matter connectivity maps from diffusion tensor imaging (DTI).  ...  Abstract Fiber tracking is the most popular technique for creating white matter connectivity maps from diffusion tensor imaging (DTI).  ...  This atlas is based on probabilistic tensor maps obtained from 81 normal subjects acquired under an initiative of the ICBM.  ... 
doi:10.1007/s12021-012-9148-z pmid:22467471 fatcat:6qqwst7iw5aytpdcfr7w4i2buq

Active delineation of Meyer's loop using oriented priors through MAGNEtic tractography (MAGNET)

Maxime Chamberland, Benoit Scherrer, Sanjay P. Prabhu, Joseph Madsen, David Fortin, Kevin Whittingstall, Maxime Descoteaux, Simon K. Warfield
2016 Human Brain Mapping  
Streamline tractography algorithms infer connectivity from diffusion MRI (dMRI) by following diffusion directions which are similarly aligned between neighbouring voxels.  ...  In this article, we demonstrate that MAGNEtic Tractography (MAGNET) can benefit Meyer's loop delineation by incorporating anatomical knowledge of the expected fiber orientation to overcome local ambiguities  ...  operative data.  ... 
doi:10.1002/hbm.23399 pmid:27647682 pmcid:PMC5333642 fatcat:7wclydvckveu5mtq5ldjem3gm4

Skeletal muscle diffusion tensor-MRI fiber tracking: rationale, data acquisition and analysis methods, applications and future directions

Bruce M. Damon, Martijn Froeling, Amanda K. W. Buck, Jos Oudeman, Zhaohua Ding, Aart J. Nederveen, Emily C. Bush, Gustav J. Strijkers
2016 NMR in Biomedicine  
The fourth section discusses methods for pre-processing DT-MRI data, the available approaches for calculating the diffusion tensor and seeding and propagating fiber tracts, and analyzing the tracking results  ...  In this review, we describe the use of diffusion-tensor (DT-) MRI muscle fiber tracking for studying muscle architecture.  ...  Most fiber tracking software allow the use of seed regions as well as whole volume (WV) seeding followed by fiber tract selection using the Boolean operators AND, NOT, and OR.  ... 
doi:10.1002/nbm.3563 pmid:27257975 pmcid:PMC5136336 fatcat:2baam6367rgjzb7urnraomnivi

New Directions in 3D Medical Modeling: 3D-Printing Anatomy and Functions in Neurosurgical Planning

Paolo Gargiulo, Íris Árnadóttir, Magnús Gíslason, Kyle Edmunds, Ingvar Ólafsson
2017 Journal of Healthcare Engineering  
The method introduced here combines CT and MRI images with DTI tractography, while using various image segmentation protocols to 3D model the skull base, tumor, and five eloquent fiber tracts.  ...  Moreover, the work presented here demonstrates the workflow developed at the National University Hospital of Iceland, Landspitali, focusing on the processes of anatomy segmentation, fiber tract extrapolation  ...  This operation is threshold based; where a range of HU (typically, from 600 to 2000) values are selected that allow to display the bone tissue.  ... 
doi:10.1155/2017/1439643 pmid:29068642 fatcat:ongsxtg2cvb5dadn5ogtsl5lsq

Tractography in the clinics: Implementing a pipeline to characterize early brain development

Fernando Yepes-Calderon, Yi Lao, Pierre Fillard, Marvin D. Nelson, Ashok Panigrahy, Natasha Lepore
2017 NeuroImage: Clinical  
In imaging studies of neonates, particularly in the clinical setting, diffusion tensor imaging-based tractography is typically unreliable due to the use of fast acquisition protocols that yield low resolution  ...  Geometrical and diffusion based features of the tracts are then utilized to compare premature babies to term babies. Our results quantify the maturation of white matter fiber tracts in neonates.  ...  As the averaging procedure is performed in the tensor domain, one the diffusion patterns overlapped with the ones found in the sample selected as the model.  ... 
doi:10.1016/j.nicl.2016.12.029 pmid:28348954 pmcid:PMC5357703 fatcat:xckmj4xowvdcrhpamzf6kk6tka

Improved tractography alignment using combined volumetric and surface registration

Lilla Zöllei, Allison Stevens, Kristen Huber, Sita Kakunoori, Bruce Fischl
2010 NeuroImage  
techniques for computing cross-subject alignment directly from the DWI data itself.  ...  In addition, we compare linear alignment using FLIRT based on either fractional anisotropy or anatomical volumes across-subjects, and find a comparable effect.  ...  Wedeen (Martinos Center for Biomedical Imaging, Massachusetts General Hospital) for Trackvis and Diffusion Toolkit, Jean Augustinack for our long discussions about neuroanatomy and Steve Smith for his  ... 
doi:10.1016/j.neuroimage.2010.01.101 pmid:20153833 pmcid:PMC2847021 fatcat:4kezark5jjfm7ldh6kcpwuzd6a

Visualizing White Matter Fiber Tracts with Optimally Fitted Curved Dissection Surfaces [article]

Ralph Schurade, Mario Hlawitschka, Bernd Hamann, Gerik Scheuermann, Thomas R. Knösche, Alfred Anwander
2010 Eurographics Workshop on Visual Computing for Biomedicine  
White matter fiber tractography from diffusion tensor imaging (DTI) is, in general, visualized as 3D lines or tubes together with 2D anatomical MR slices or surfaces.  ...  An optimal view on the naturally embedding curved anatomical structure of the surrounding tissue enables the study of location and course of fiber bundles and the specific relation between different fiber  ...  A selection of fibers can be provided by, for example, Boolean operations applied to fibers intersecting different boxes, indicated by green rectangles here. tion (Fig. 2 ).  ... 
doi:10.2312/vcbm/vcbm10/041-048 fatcat:obxarxssb5h5tmqx2bk54czbhi

The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software

Blake C. Lucas, John A. Bogovic, Aaron Carass, Pierre-Louis Bazin, Jerry L. Prince, Dzung L. Pham, Bennett A. Landman
2010 Neuroinformatics  
With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation.  ...  Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis  ...  Once selected from this menu, a programmatically generated GUI appears for any tool (C) which can operate on any image accessible to MIPAV. Figure 2 . 2 Figure 2. Figure 3 . 3 Figure 3.  ... 
doi:10.1007/s12021-009-9061-2 pmid:20077162 pmcid:PMC2860951 fatcat:i3jilk4wjfdn7nr4t3uospc3u4

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Jeffrey S. Phillips, Adam S. Greenberg, John A. Pyles, Sudhir K. Pathak, Marlene Behrmann, Walter Schneider, Michael J. Tarr
2012 Journal of Visualized Experiments  
The results compare favorably with one of the most widely-used techniques in DWI, diffusion tensor imaging (DTI).  ...  Structural imaging is performed with diffusion-weighted imaging (DWI) and fiber tractography, which track the diffusion of water molecules along white-matter fiber tracts in the brain (Figure 1).  ...  Based on these data, diffusion patterns are typically modeled with a simple tensor model, which is best suited for detecting a single dominant diffusion direction.  ... 
doi:10.3791/4125 pmid:23169034 pmcid:PMC3520572 fatcat:vr5zlgo4kzfm7ggwzwjadf7h2m

Spatial mapping of translational diffusion coefficients using diffusion tensor imaging: A mathematical description

Anil N. Shetty, Sharon Chiang, Mirjana Maletic-Savatic, Gregor Kasprian, Marina Vannucci, Wesley Lee
2014 Concepts in magnetic resonance. Part A, Bridging education and research  
The anisotropy is analyzed by decomposing the diffusion tensor based on symmetrical properties describing the geometry of diffusion tensor.  ...  Thus, it is possible to generate contrast in tissue based primarily on diffusion effects.  ...  After tractography is performed, tracks can be required to pass through multiple ROIs drawn using Boolean operators.  ... 
doi:10.1002/cmr.a.21288 pmid:27441031 pmcid:PMC4948124 fatcat:o7vvzbfawvfa3aazysx46swpsu

Exploring Connectivity of the Brain's White Matter with Dynamic Queries

A. Sherbondy, D. Akers, R. Mackenzie, R. Dougherty, B. Wandell
2005 IEEE Transactions on Visualization and Computer Graphics  
These regions can be used in coordination with a simple and flexible query language which allows for arbitrary combinations of these queries using Boolean logic operators.  ...  Abstract-Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging method that can be used to measure local information about the structure of white matter within the human brain.  ...  ACKNOWLEDGMENTS We thank Roland Bammer and Michael Moseley of the Stanford University Lucas Center, for useful discussions and for developing the pulse sequences used to collect our data.  ... 
doi:10.1109/tvcg.2005.59 pmid:16138552 fatcat:wz4llh6jjna7dokqxy4kedroyq

The role of preoperative diffusion tensor imaging in predicting and improving functional outcome in pediatric patients undergoing epilepsy surgery: a systematic review

Jose Leon-Rojas, Isabel Cornell, Antonio Rojas-Garcia, Felice D'Arco, Jasmina Panovska-Griffiths, Helen Cross, Sotirios Bisdas
2021 BJR|Open  
Objective: Diffusion tensor imaging (DTI) is a useful neuroimaging technique for surgical planning in adult patients.  ...  Data extraction was performed by two blinded reviewers. Risk of bias of each study was determined using the QUADAS 2 Scoring System.  ...  Pooled data regarding sensitivity and specificity of quantitative DTI values for prediction of post-operative motor outcome. 10 DTI, diffusion tensor imaging.  ... 
doi:10.1259/bjro.20200002 pmid:34381942 pmcid:PMC8320117 fatcat:bvieabukafbmrih7omzgoheesy

A graph-based approach for automatic cardiac tractography

Carole Frindel, Marc Robini, Joël Schaerer, Pierre Croisille, Yue-Min Zhu
2010 Magnetic Resonance in Medicine  
Besides, seed points are no longer needed; fibers are predicted in one shot for the whole diffusion-tensor magnetic resonance imaging volume, in a completely automatic way.  ...  A new automatic algorithm for assessing fiber-bundle organization in the human heart using diffusion-tensor magnetic resonance imaging is presented.  ...  The direction of the line segment is chosen based on some local function of the data such as the eigenvector with largest eigenvalue of the diffusion tensor (1) (2) (3) or the direction maximizing an  ... 
doi:10.1002/mrm.22443 pmid:20665895 fatcat:4ie2hvwqijhsjgux7gysp5xd2u
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