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Unsupervised white matter fiber clustering and tract probability map generation: Applications of a Gaussian process framework for white matter fibers
2010
NeuroImage
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Subsequently, the applicability of the unsupervised clustering framework has been demonstrated on a 21 subject dataset. ...
of white matter fiber bundles incorporating their underlying physical significance. ...
A Gaussian Process framework for white matter fibers Gaussian Processes (GP) are a rich mathematical framework that has been used in a wide variety of research fields. ...
doi:10.1016/j.neuroimage.2010.01.004
pmid:20079439
pmcid:PMC2847030
fatcat:elivlqvdbre4jlq2tpplvds3nm
Unsupervised classification of skeletal fibers using diffusion maps
2009
2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
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In this paper, we propose an application of diffusion maps to fiber tract clustering in the human skeletal muscle. ...
This metric is incorporated in the diffusion maps framework and clustering is done in the embedding space using k-means. ...
A METRIC BETWEEN FIBER TRACTS Instead of considering a fiber tract as a set of points, we will view it as a set of Gaussian probability distributions. ...
doi:10.1109/isbi.2009.5193071
dblp:conf/isbi/NejiLDMRBFP09
fatcat:dfhxeu55vne7npjghdouknhxbi
Atlas-Guided Cluster Analysis of Large Tractography Datasets
2013
PLoS ONE
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Structural information of a white matter atlas can be incorporated into the clustering to achieve an anatomically correct and reproducible grouping of fiber tracts. ...
As the fast and consistent extraction of anatomically correct fiber bundles for multiple datasets is still challenging, we present a novel atlasguided clustering framework for exploratory data analysis ...
In their framework tracts are successively formed and the Gaussian processes of the tracts are merged in each iteration. ...
doi:10.1371/journal.pone.0083847
pmid:24386292
pmcid:PMC3875498
fatcat:sqf2jvlrzrhefg3wiquo6w7kaq
Automatic Tractography Segmentation Using a High-Dimensional White Matter Atlas
2007
IEEE Transactions on Medical Imaging
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The white matter clusters are augmented with expert anatomical labels and stored in a new type of atlas that we call a high-dimensional white matter atlas. ...
We propose a new white matter atlas creation method that learns a model of the common white matter structures present in a group of subjects. ...
ACKNOWLEDGMENT The authors would like to thank Lilla Zollei for the congealing registration code and W. Eric L. ...
doi:10.1109/tmi.2007.906785
pmid:18041271
fatcat:rmbeixyqujcj3b4utpdqjwn4uu
A mathematical framework for incorporating anatomical knowledge in DT-MRI analysis
2008
2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro
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The proposed approach provides a robust and automated tool for tract-oriented analysis both in a single subject and over a population. ...
We propose a Bayesian approach to incorporate anatomical information in the clustering of fiber trajectories. ...
Most recently, an atlas-based quantitative analysis of white matter fiber tracts has been proposed in which a probabilistic parcellation map of the tracts is used to obtain the weighted average of the ...
doi:10.1109/isbi.2008.4540943
pmid:19212449
pmcid:PMC2638065
dblp:conf/isbi/MaddahZGWW08
fatcat:tk65bn2dwndilcpuwnhfrtuvzu
Diffusion Tensor Imaging and Its Application to Traumatic Brain Injury: Basic Principles and Recent Advances
2012
Open Journal of Medical Imaging
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Diffusion MRI tractography is an extension of diffusion weighted imaging, and can provide additional information about white matter pathways and the integrity of brain neural networks. ...
Traumatic axonal injury is a progressive process evoked by shear forces on the brain, gradually evolving from focal axonal alteration and cumulating in neural disconnection. ...
All of these unsupervised clustering techniques must integrate anatomic knowledge and atlas information in order to parcellate the known meaningful fiber tracts. ...
doi:10.4236/ojmi.2012.24025
fatcat:h55evmhkkndapaczqmptddpguu
Unsupervised clustering of track-weighted dynamic functional connectivity reveals white matter substrates of functional connectivity dynamics
[article]
2021
bioRxiv
pre-print
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Each component consisted of a spatial map of white matter bundles that show consistent fluctuations in functional connectivity at their endpoints, and a time course representative of such functional activity ...
The tw-dFC maps were analyzed using independent component analysis, aiming at identifying spatially independent white matter components which support dynamic changes in functional connectivity. ...
A one sample t-test was run to generate group statistical maps for each component's SM, and a hard parcellation of the white matter was obtained by thresholding the obtained t-maps at z=1. ...
doi:10.1101/2021.12.04.471233
fatcat:r5bzfn7je5fnjosuh7a47f5iju
Longitudinal deterioration of white matter integrity: heterogeneity in the aging population
2021
Brain Communications
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Identification of vulnerable white matter tracts is a valuable approach to assessing risk for cognitive decline. ...
Clusters had differential white matter tract vulnerability to aging (commissural fibers>association/brainstem fibers). ...
We thank all the study participants and staff of the MCSA, Mayo Alzheimer's Disease Research Center, and Aging Dementia Imaging Research Laboratory at the Mayo Clinic for making this study possible. ...
doi:10.1093/braincomms/fcaa238
pmid:33615218
pmcid:PMC7884606
fatcat:v4iyd3p2fnfndk55ia4fd2lari
Independent component analysis tractography combined with a ball-stick model to isolate intravoxel crossing fibers of the corticospinal tracts in clinical diffusion MRI
2012
Magnetic Resonance in Medicine
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A common problem encountered in the streamline tractography of white matter fiber systems when relying on a rank-2 diffusion tensor model (1,2) is the existence of multiple fiber orientations within an ...
Especially at the boundary of different white matter regions where multiple fibers likely cross only at some voxels of the cluster, the sensitivity of the ICA decomposition might be significantly reduced ...
ACKNOWLEDGMENTS This study was partially funded by a grant from the NIH to E.A. ...
doi:10.1002/mrm.24487
pmid:23001816
pmcid:PMC3657599
fatcat:suy6v2ggvbgtbkpfhxvbylc6hu
Nonparametric Bayes Models of Fiber Curves Connecting Brain Regions
[article]
2016
arXiv
pre-print
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The approach automatically produces clusters of fibers within and across individuals, and yields interesting new insights into variation in fiber curves, while providing a useful starting point for more ...
Current statistical methods for analyzing these fibers reduce the rich information into an adjacency matrix, with the elements containing a count of the number of fibers or a mean diffusion feature (such ...
) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. ...
arXiv:1612.01014v1
fatcat:7sybplthbzdytduyujlhvkk7l4
Association between Structural Connectivity and Generalized Cognitive Spectrum in Alzheimer's Disease
2020
Brain Sciences
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We developed a machine learning framework to find a generalized cognitive score that summarizes the different functional domains reflected by each cognitive clinical index and to identify the connectivity ...
conditions of the patients and are commonly used as objective criteria for clinical diagnosis of dementia and mild cognitive impairment (MCI). ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/brainsci10110879
pmid:33233622
fatcat:e7ltzftd2zelzg7ipjct4e73zy
Segmentation of High Angular Resolution Diffusion MRI Using Sparse Riemannian Manifold Clustering
2014
IEEE Transactions on Medical Imaging
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Experiments on phantom and real data demonstrate the accuracy of the proposed method in segmenting simulated fibers and white matter fiber tracts of clinical importance. ...
By exploiting the Riemannian properties of the space of ODFs, we learn a sparse representation for each ODF and infer the segmentation by applying spectral clustering to a similarity matrix built from ...
McMahon and G. I. de Zubicaray at the Centre for Magnetic Resonance, University of Queensland for agreeing to share the brain image data. H. ...
doi:10.1109/tmi.2013.2284360
pmid:24108748
pmcid:PMC4293082
fatcat:3yvye35m2beh3fzsp4s3uq32e4
Robust thalamic nuclei segmentation method based on local diffusion magnetic resonance properties
2016
Brain Structure and Function
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We present a novel framework for segmenting the thalamic nuclei, which explores the orientation distribution functions (ODFs) from diffusion magnetic resonance images at 3 T. ...
process in each voxel. ...
, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. ...
doi:10.1007/s00429-016-1336-4
pmid:27888345
pmcid:PMC5504280
fatcat:cg53upqwzja6vfylbh6gwcays4
Multidisciplinary Approaches to Multivalued Data: Modeling, Visualization, Analysis (Dagstuhl Seminar 16142)
2016
Dagstuhl Reports
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Novel tools for image analysis, visualization, as well as statistical hypothesis testing and machine learning are required to extract value from such data, and can only be developed within multidisciplinary ...
This report gathers abstracts of the talks held by participants on recent advances and open questions related to these challenges, as well as an account of topics raised within two of the breakout sessions ...
white matter. ...
doi:10.4230/dagrep.6.4.16
dblp:journals/dagstuhl-reports/HotzO016
fatcat:tlx6mmmairgfpgs4mx7dndy5n4
The quest for biomarkers in Schizophrenia: from neuroimaging to machine learning
2017
International Journal of Clinical Neurosciences and Mental Health
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Schizophrenia is a severe mental disorder and one of the leading causes of disease burden worldwide. ...
This situation causes overlapping of the boundaries of the diagnostic categories and constitutes a source of diagnostic errors. ...
brain imposed by white matter fiber tracts, allowing these tracts to be delineated [45] . ...
doi:10.21035/ijcnmh.2017.4(suppl.3).s03
fatcat:usbvu4ar3bfk7jjnchvjftfd6q
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