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MR Diffusion-Based Inference of a Fiber Bundle Model from a Population of Subjects [chapter]

V. El Kouby, Y. Cointepas, C. Poupon, D. Rivière, N. Golestani, J. -B. Poline, D. Le Bihan, J. -F. Mangin
2005 Lecture Notes in Computer Science  
This paper proposes a method to infer a high level model of the white matter organization from a population of subjects using MR diffusion imaging.  ...  The method is applied on a population of eleven subjects and leads to the inference of 17 such candidates.  ...  There is a need for computational methods aiming at infering a model of the main bundles making up the human brain white matter from MR diffusion imaging.  ... 
doi:10.1007/11566465_25 fatcat:ewhs5zwmjjcwbgxpdbrlqz462u

Parametric spherical deconvolution: Inferring anatomical connectivity using diffusion MR imaging

Enrico Kaden, Thomas R. Knösche, Alfred Anwander
2007 NeuroImage  
In this article we propose a new forward model that maps the microscopic geometry of nervous tissue onto the water diffusion process and further onto the measured MR signals.  ...  The advent of diffusion MR imaging has enabled the exploration of the structural properties of white matter in vivo.  ...  Acknowledgments The authors thank Timm Wetzel for providing the diffusionweighted MR data set. Moreover, E.K. is grateful to Gabriele Lohmann for valuable advice and fruitful discussions.  ... 
doi:10.1016/j.neuroimage.2007.05.012 pmid:17596967 fatcat:qa7audizcnhplavb6c3mfkvctq

Robust clustering of massive tractography datasets

P. Guevara, C. Poupon, D. Rivière, Y. Cointepas, M. Descoteaux, B. Thirion, J.-F. Mangin
2011 NeuroImage  
This paper presents a clustering method that detects the fiber bundles embedded in any MR-diffusion based tractography dataset.  ...  An important application will be the inference of detailed models of the subdivisions of white matter pathways and the mapping of the main U-fiber bundles.  ...  But the most important application is the inference of a brain fiber bundle model from an inter-subject analysis, which is our next research program (Guevara et al., 2010) .  ... 
doi:10.1016/j.neuroimage.2010.10.028 pmid:20965259 fatcat:kockuz3zezexrjmp7r263uvu54

Unsupervised white matter fiber clustering and tract probability map generation: Applications of a Gaussian process framework for white matter fibers

D. Wassermann, L. Bloy, E. Kanterakis, R. Verma, R. Deriche
2010 NeuroImage  
This metric facilitates combination of fiber tracts, rendering operations like tract membership to a bundle or bundle similarity simple.  ...  of white matter fiber bundles incorporating their underlying physical significance.  ...  These two functions are inferred from the tractography of each fiber.  ... 
doi:10.1016/j.neuroimage.2010.01.004 pmid:20079439 pmcid:PMC2847030 fatcat:elivlqvdbre4jlq2tpplvds3nm

Nonparametric Bayesian inference of the fiber orientation distribution from diffusion-weighted MR images

Enrico Kaden, Frithjof Kruggel
2012 Medical Image Analysis  
However, the inverse problem, i.e., the spherical deconvolution of the fiber orientation density from noisy MR measurements, is ill-posed.  ...  Diffusion MR imaging provides a unique tool to probe the microgeometry of nervous tissue and to explore the wiring diagram of the neural connections noninvasively.  ...  Acknowledgment The diffusion-weighted MR dataset analyzed in the present study was kindly provided by the 2009 Pittsburgh Brain Connectivity Competition (Schneider, 2009) , available online at http://  ... 
doi:10.1016/ pmid:22381587 fatcat:6tyopzocarapzdppqvlve3m4ue

Processing and Visualization of Diffusion MRI [chapter]

James G. Malcolm, Yogesh Rathi, Carl-Fredrik Westin
2010 Biomedical Image Processing  
We describe various approaches to modeling the local diffusion structure from scanner measurements. We then look at techniques to trace out neural pathways and infer global tissue structure.  ...  This chapter provides a survey of techniques for processing and visualization of diffusion magnetic resonance imagery.  ...  bundles from individual fiber traces, and analyze groups of individuals.  ... 
doi:10.1007/978-3-642-15816-2_16 fatcat:uqcj676gbzc3fkqlk6vwep3mfm

White matter integrity, fiber count, and other fallacies: The do's and don'ts of diffusion MRI

Derek K. Jones, Thomas R. Knösche, Robert Turner
2013 NeuroImage  
In order to encourage the use of improved DW-MRI methods, which have a better chance of characterizing the actual fiber structure of white matter, and to warn against the misuse and misinterpretation of  ...  An early form of this technique, diffusion tensor imaging (DTI) was rapidly implemented by major MRI scanner companies as a scanner selling point.  ...  If use of a FLAIR-based diffusion-weighted MR acquisition is appropriate, then this could be utilized.  ... 
doi:10.1016/j.neuroimage.2012.06.081 pmid:22846632 fatcat:4vw3xz3u4rdyhf2fi7rrwo43hu

Physical and digital phantoms for validating tractography and assessing artifacts

Ivana Drobnjak, Peter Neher, Cyril Poupon, Tabinda Sarwar
2021 NeuroImage  
It is well-known that the indirect estimation of the fiber tracts from the local diffusion signal is highly ambiguous and extremely challenging.  ...  Fiber tractography is widely used to non-invasively map white-matter bundles in vivo using diffusion-weighted magnetic resonance imaging (dMRI).  ...  underlying fiber populations.  ... 
doi:10.1016/j.neuroimage.2021.118704 pmid:34748954 fatcat:zygzq576lnhqxekoixpnc4y3pq

Tractography segmentation using a hierarchical Dirichlet processes mixture model

Xiaogang Wang, W. Eric L. Grimson, Carl-Fredrik Westin
2011 NeuroImage  
After the models of bundles have been learned from training data without supervision, they can be used as priors to cluster/classify fibers of new subjects for comparison across subjects.  ...  In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model.  ...  Given fibers of new subjects observed, the models of bundles learned from the training set are updated and fibers of new subjects are clustered based on the updated models.  ... 
doi:10.1016/j.neuroimage.2010.07.050 pmid:20678578 pmcid:PMC2962770 fatcat:yssreirs75f3dn25whhrxmsfze

Tractography Segmentation Using a Hierarchical Dirichlet Processes Mixture Model [chapter]

Xiaogang Wang, W. Eric L. Grimson, Carl-Fredrik Westin
2009 Lecture Notes in Computer Science  
After the models of bundles have been learned from training data without supervision, they can be used as priors to cluster/classify fibers of new subjects for comparison across subjects.  ...  In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model.  ...  Given fibers of new subjects observed, the models of bundles learned from the training set are updated and fibers of new subjects are clustered based on the updated models.  ... 
doi:10.1007/978-3-642-02498-6_9 fatcat:5lejhqe6mzdwxnhneakac5tzta

Short superficial white matter and aging: a longitudinal multi-site study of 1,293 subjects and 2,711 sessions [article]

Kurt G Schilling, Derek B Archer, Fang-Cheng Yeh, Francois Rheault, Leon Y Cai, Andrea Shafer, Susan M Resnick, Timothy Hohman, Angela Jefferson, Adam W Anderson, Hakmook Kang, Bennett A Landman
2022 bioRxiv   pre-print
into the biological foundation of age-related cognitive changes, and a better understanding of how age-related pathology differs from healthy aging.  ...  This is largely because of limitations of diffusion MRI fiber tractography, which is the primary methodology used to non-invasively study the white matter connections.  ...  U-fiber systems show expected shape and locations, and cover a large portion of the surface of the brain. 82 U-fibers determined to be robust across a population are shown in a single subject, with distinct  ... 
doi:10.1101/2022.06.06.494720 fatcat:n2hxdeq6h5cepcvdlh5cstohuy

Magnetic Resonance Connectome Automated Pipeline [article]

William R. Gray, John A. Bogovic, Joshua T. Vogelstein, Bennett A. Landman, Jerry L. Prince, R. Jacob Vogelstein
2011 arXiv   pre-print
MRCAP will enable MR connectomes to be rapidly generated to ultimately help spur discoveries about the structure and function of the human brain.  ...  This manuscript presents a novel, tightly integrated pipeline for estimating a connectome, which is a comprehensive description of the neural circuits in the brain.  ...  A. Input Data The pipeline accepts the diffusion and structural MR data from a subject, the associated metadata, and user-specified parameters as inputs.  ... 
arXiv:1111.2660v1 fatcat:c6kvot3gf5e3xofdhb2ofthb6i

FRATS: Functional Regression Analysis of DTI Tract Statistics

Hongtu Zhu, M. Styner, Niansheng Tang, Zhexing Liu, Weili Lin, J.H. Gilmore
2010 IEEE Transactions on Medical Imaging  
model for characterizing the association between fiber bundle diffusion properties and a set of covariates, a global test statistic for testing hypotheses of interest, and a resampling method for approximating  ...  Diffusion tensor imaging (DTI) provides important information on the structure of white matter fiber bundles as well as detailed tissue properties along these fiber bundles in vivo.  ...  FRATS: Nonparametric Model After spatial normalization of tensor images, we propose to use a functional regression model to analyze diffusion properties along the same fiber bundle from multiple subjects  ... 
doi:10.1109/tmi.2010.2040625 pmid:20335089 pmcid:PMC2896997 fatcat:3s2qsd2lrfgizfn24nwzi3u3ra

Connectivity-Based Parcellation of the Cortical Mantle Usingq-Ball Diffusion Imaging

Muriel Perrin, Yann Cointepas, Arnaud Cachia, Cyril Poupon, Bertrand Thirion, Denis Rivière, Pascal Cathier, Vincent El Kouby, André Constantinesco, Denis Le Bihan, Jean-François Mangin
2008 International Journal of Biomedical Imaging  
Fiber ODF are inferred from theq-balls using a sharpening process focusing the weight around theq-ball local maxima.  ...  A sophisticated mask of propagation computed from a T1-weighted image perfectly aligned with the diffusion data prevents the particles from crossing the cortical folds.  ...  The fiber orientation can be inferred from this anisotropy.  ... 
doi:10.1155/2008/368406 pmid:18401457 pmcid:PMC2288697 fatcat:7pgunwf7c5guvem33loc5zbcv4

Automated delineation of white matter fiber tracts with a multiple region-of-interest approach

Ralph O. Suarez, Olivier Commowick, Sanjay P. Prabhu, Simon K. Warfield
2012 NeuroImage  
In a study of 20 healthy volunteers, we compared three methodologies for automated delineation of the white matter fiber bundles.  ...  Manual identification of anatomical MROI enables the delineation of white matter fiber bundles, but requires considerable training to develop expertise, considerable time to carry out and suffers from  ...  Acknowledgments This investigation was supported in part by National Institutes of Health grants R01 RR021885, R01 EB008015, R03 EB008680, R01 LM010033, and by a pilot grant from The National Multiple  ... 
doi:10.1016/j.neuroimage.2011.11.043 pmid:22155046 pmcid:PMC3302580 fatcat:m7c7eejwibawdngvls2pppenly
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