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Spatial Normalization and Averaging of Diffusion Tensor MRI Data Sets

D Jones
2002 NeuroImage  
., the spatial normalization of whole tensor data sets. The approach is illustrated by spatial normalization of 10 DT-MRI data sets to a standard anatomical template.  ...  Techniques are then described for combining the spatially normalized data sets according to three definitions of average, i.e., the mean, median, and mode of a distribution of tensors.  ...  Carlo Pierpaoli (Laboratory of Integrative and Medical Biophysics, National Institutes of Health, Bethesda, MD), for early and informative discussions regarding spatial normalization of DT-MRI data, and  ... 
doi:10.1016/s1053-8119(02)91148-1 pmid:12377137 fatcat:nfmw3u6punerpelue3tflbjqfu

Spatial Normalization and Averaging of Diffusion Tensor MRI Data Sets

Derek K. Jones, Lewis D. Griffin, Daniel C. Alexander, Marco Catani, Mark A. Horsfield, Robert Howard, Steve C.R. Williams
2002 NeuroImage  
., the spatial normalization of whole tensor data sets. The approach is illustrated by spatial normalization of 10 DT-MRI data sets to a standard anatomical template.  ...  Techniques are then described for combining the spatially normalized data sets according to three definitions of average, i.e., the mean, median, and mode of a distribution of tensors.  ...  Carlo Pierpaoli (Laboratory of Integrative and Medical Biophysics, National Institutes of Health, Bethesda, MD), for early and informative discussions regarding spatial normalization of DT-MRI data, and  ... 
doi:10.1006/nimg.2002.1148 pmid:12377137 fatcat:mzltwgapenbrdod7b3qjor6nxe

A framework for spatial normalization and voxelwise analysis of diffusion propagators in multiple MAP-MRI data sets [article]

Alexandru V Avram, Adam S Bernstein, M. Okan Irfanoglu, Craig C. Weinkauf, Martin Cota, Neville Gai, Amber Simmons, Anita Moses, L. Christine Turtzo, Neekita Jikaria, Lawrence Latour, Dzung Pham (+2 others)
2019 bioRxiv   pre-print
The pipeline leverages the fact that MAP-MRI is a generalization of diffusion tensor imaging (DTI) and combines simple and robust processing steps from existing tensor-based image registration methods.  ...  Next, we transform each diffusion data set, including diffusion weighted images (DWIs) and gradient directions, from native to template space using the corresponding tensor-based deformation fields.  ...  Nevertheless, both cross-sectional and single-subject longitudinal studies require adequate tools for accurate spatial normalization and analysis of multiple MAP-MRI data sets.  ... 
doi:10.1101/697284 fatcat:tpczdf43qbgcddf6txr7om4mty

Tensor Field Regularization Using Normalized Convolution [chapter]

Carl-Fredrik Westin, Hans Knutsson
2003 Lecture Notes in Computer Science  
A driving application for this work has been filtering of data from Diffusion Tensor MRI.  ...  We use a nonlinear filtering technique termed normalized convolution [Knutsson and Westin 1993], a general method for filtering missing and uncertain data.  ...  This work was funded in part by NIH grant P41-RR13218, R01-MH 50747 and CIMIT.  ... 
doi:10.1007/978-3-540-45210-2_51 fatcat:6cx5u3o32jgxnemlnjyq44dm3y

Spatial normalization of diffusion tensor MRI using multiple channels

H Park
2003 NeuroImage  
In this article, we used a multiple input channel registration algorithm based on a demons algorithm and evaluated the spatial normalization of diffusion tensor image in terms of the input information  ...  Registration was performed on 16 DT-MRI data sets using different combinations of the channels, including a channel of T2-weighted intensity, a channel of the fractional anisotropy, a channel of the difference  ...  Additionally, we gratefully acknowledge the support of the Post  ... 
doi:10.1016/j.neuroimage.2003.08.008 pmid:14683705 pmcid:PMC2811885 fatcat:kual3f34lfdnrgttgmzam6taaa

MAGNETIC RESONANCE WATER SELF-DIFFUSION TENSOR ENCODING OPTIMIZATION METHODS FOR FULL BRAIN ACQUISITION

Khader M Hasan, Dennis L Parker, Andrew L Alexander
2011 Image Analysis and Stereology  
The DT-MRI experiment involves a host of imaging and diffusion parameters that influence the efficiency (signal-to-noise ratio per unit time), accuracy, and specificity of the information sought.  ...  Water diffusion tensor magnetic resonance imaging (DT-MRI) is a non-invasive and sensitive modality that is becoming increasingly popular in diagnostic radiology.  ...  ACKNOWLEDGMENTS This work was funded by the American National Institute of Health Grant NIMH R01-6215. The editorial assistance of Marci Harris and Michael Anderle is appreciated.  ... 
doi:10.5566/ias.v21.p87-96 fatcat:vmm3aw42brhufmbr2dulfvbah4

A Continuous Tensor Field Approximation of Discrete DT-MRI Data for Extracting Microstructural and Architectural Features of Tissue

Sinisa Pajevic, Akram Aldroubi, Peter J. Basser
2002 Journal of magnetic resonance (San Diego, Calif. 1997 : Print)  
The effective diffusion tensor of water, D , measured by diffusion tensor MRI (DT-MRI), is inherently a discrete, noisy, voxelaveraged sample of an underlying macroscopic effective diffusion tensor field  ...  The fidelity and noiseimmunity of this approximation are tested using a set of synthetically generated tensor fields to which background noise is added via Monte Carlo methods.  ...  We also thank Jeffrey Duda-a former summer student in our laboratory-for implementing early versions of several of these tensor field approximation algorithms in IDL.  ... 
doi:10.1006/jmre.2001.2452 pmid:11820830 fatcat:z5ftlvkvpjahzh4gtbswmhw56q

Microstructural Infarct Border Zone Remodeling in the Post-infarct Swine Heart Measured by Diffusion Tensor MRI

Geoffrey L. Kung, Marmar Vaseghi, Jin K. Gahm, Jane Shevtsov, Alan Garfinkel, Kalyanam Shivkumar, Daniel B. Ennis
2018 Frontiers in Physiology  
Diffusion tensor MRI (DT-MRI) can evaluate microstructural remodeling by quantifying the DT apparent diffusion coefficient (ADC, increased with decreased cellularity), fractional anisotropy (FA, decreased  ...  Conclusion: DT-MRI can identify regions of significant microstructural remodeling in the BZ that are distinct from both remote and infarcted myocardium.  ...  AUTHOR CONTRIBUTIONS All authors contributed to the study conception and design. GK, MV, and DE were responsible for acquisition of data.  ... 
doi:10.3389/fphys.2018.00826 pmid:30246802 pmcid:PMC6113632 fatcat:bghr5ex7lzbo7nc2busq7prrv4

A review of diffusion tensor magnetic resonance imaging computational methods and software tools

Khader M. Hasan, Indika S. Walimuni, Humaira Abid, Klaus R. Hahn
2011 Computers in Biology and Medicine  
A review of different methods used to acquire, model and analyze diffusion-weighted imaging data (DWI) is first provided with focus on diffusion tensor imaging (DTI).  ...  In this work we provide an up-to-date short review of computational magnetic resonance imaging (MRI) and software tools that are widely used to process and analyze diffusion-weighted MRI data.  ...  Acknowledgments This work is funded by the NIH-NINDS Grant R01 NS052505-04 and the Dunn Fund.  ... 
doi:10.1016/j.compbiomed.2010.10.008 pmid:21087766 pmcid:PMC3135778 fatcat:osm25rvelrgb3ddhogdfnl4y6a

Time-Optimized High-Resolution Readout-Segmented Diffusion Tensor Imaging

Gernot Reishofer, Karl Koschutnig, Christian Langkammer, David Porter, Margit Jehna, Christian Enzinger, Stephen Keeling, Franz Ebner, Christian Beaulieu
2013 PLoS ONE  
Tractography from in vivo data and from a software phantom demonstrate the advantage of the spatially varying regularization compared to un-regularized data with respect to parameters relevant for fiber-tracking  ...  Moreover, the combination of those features enables processing of the diffusion data absolutely user independent.  ...  For further processing, data sets from one, two and three averages were evaluated separately.  ... 
doi:10.1371/journal.pone.0074156 pmid:24019951 pmcid:PMC3760803 fatcat:q3nzpnlnpbavvh2pitzkebfsh4

Interface Detection in Diffusion Tensor MRI [chapter]

Lauren O'Donnell, W. Eric L. Grimson, Carl-Fredrik Westin
2004 Lecture Notes in Computer Science  
The local structure tensor provides a rotationally invariant description of edge orientation, and its shape after local averaging describes the type of edge.  ...  Additionally, due to the higher dimensionality of tensor data, humans are visually unable to detect edges as easily as in scalar data, so edge detection has potential applications in diffusion tensor visualization  ...  Acknowledgments We would like to thank the HST Neuroimaging Training Grant, NSF ERC CISST 8810-27499, and NAC grant number NIH P41 RR 13218.  ... 
doi:10.1007/978-3-540-30135-6_44 fatcat:x2c56cteqfbdtde3nvflcymz3m

Towards analysis of growth trajectory through multimodal longitudinal MR imaging

Neda Sadeghi, Marcel Prastawa, John H. Gilmore, Weili Lin, Guido Gerig, David R. Haynor, Benoit M. Dawant
2010 Medical Imaging 2010: Image Processing  
We demonstrate that the combined longitudinal analysis of structural and diffusion MRI proves superior to individual modalities and might provide a better understanding of the trajectory of early neurodevelopment  ...  Analysis is driven by the registration of multiple modalities and time points within and between subjects into a common coordinate frame, followed by image intensity normalization.  ...  Diagram of registration of multi-modal longitudinal data is shown in Figure 1 Intersubject Spatial Normalization Comparison of structural and diffusion properties in multiple subjects requires a  ... 
doi:10.1117/12.844526 pmid:24353376 pmcid:PMC3864929 dblp:conf/miip/SadeghiPGLG10 fatcat:4qkd63crrbbonj4grjkuopvjne

Affine Coregistration of Diffusion Tensor Magnetic Resonance Images Using Mutual Information [chapter]

Alexander Leemans, Jan Sijbers, Steve De Backer, Everhard Vandervliet, Paul M. Parizel
2005 Lecture Notes in Computer Science  
Also, in addition to the coregistration of the DT-MRI data sets, an appropriate reorientation of the diffusion tensor is worked out in order to remain consistent with the corresponding underlying anatomical  ...  In this paper, we present an affine image coregistration technique for Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) data sets based on mutual information.  ...  Further image processing of the DT-MRI data sets, i.e. calculation of the diffusion tensor and the direction color-encoded maps, was performed with 'ExploreDTI', a graphical toolbox for exploratory DT-MRI  ... 
doi:10.1007/11558484_66 fatcat:f7i4z2kbjzg3fn22pkaqvmpige

Novel image processing techniques to better understand white matter disruption in multiple sclerosis

Daniel Goldberg-Zimring, Simon K. Warfield
2006 Autoimmunity Reviews  
obtained from a set of subjects, and Tractographies which can aid in the delineation of WM fiber tracts by tracking connected diffusion tensors.  ...  Diffusion tensor MRI (DT-MRI) can provide important in-vivo information about fiber direction that is not provided by conventional MRI.  ...  Abnormalities of normal appearing white matter (NAWM) on T2-weighted MRI have been detected using magnetization transfer (MT) imaging [1, 2] , diffusion tensor MRI (DT-MRI) [3] [4] [5] [6] [7] and MR  ... 
doi:10.1016/j.autrev.2006.06.003 pmid:17027890 fatcat:uuq4adh3fzfzdpwd7qhfmpsm2a

Noise considerations in the determination of diffusion tensor anisotropy

Stefan Skare, Tie-Qiang Li, Bo Nordell, Martin Ingvar
2000 Magnetic Resonance Imaging  
In this study the noise sensitivity of various anisotropy indices has been investigated by Monte-Carlo computer simulations and magnetic resonance imaging (MRI) measurements in a phantom and 5 healthy  ...  To reduce the partial volume effect caused by the spatial averaging with neighboring voxels, an averaging method in the time domain based on the orientation coherence of eigenvectors in repeated experiments  ...  Glover and M. E. Moseley have been helpful. The 3T MRI measurements were conducted at Lucas MRS Center, Department of Radiology, Stanford University. T. Q. Li was supported by NIH NCRR P-41 09784.  ... 
doi:10.1016/s0730-725x(00)00153-3 pmid:10930775 fatcat:rrwck6ezjva5thr544ncfuzqri
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