This anatomical substrate supports the emergence of the coherent physiological activities in the distant brain regions that make up a functional network. Pdf surface multivariate tensorbased morphometry on. Thompsons phone number, address, hospital affiliations and more. We used dictionary learning and sparse coding to effectively reduce. Pdf multivariate statistics of the jacobian matrices in. Based on the deformation field between a pair of images within the subject, the voxelwise volume change ratio jacobian determinant jd was calculated using an inhouse tensorbased morphometry algorithm kim et al.
Rooted in the riemannian geometry, conformal geometry and hyperbolic geometry, a series of algorithms, including multivariate tensorbased morphometry, surface conformal parameteriza. Tensorbased morphometry tbm 7, 4 tends to examine spatial derivatives of the deformation maps registering brains to common template, constructing morpho. Tensorbased morphometry tbm is a neuroimaging method to assess regional differences in brain structure based on the jacobian determinant of the deformation matrix. Citeseerx document details isaac councill, lee giles, pradeep teregowda. Applying modern geometry in neuroimaging research school. In 2009 ieee 12th international conference on computer vision, iccv 2009 pp. Applying sparse coding to surface multivariate tensorbased morphometry to predict future cognitive decline proc ieee int symp biomed imaging. Surface multivariate tensorbased morphometry on premature. Voxelbased morphometry vbm and tensorbased morphometry tbm both rely on spatial normali. Feature selective temporal prediction of alzheimers. Tensorbased morphometry as a neuroimaging biomarker for.
Applying sparse coding to surface multivariate tensorbased morphometry to predict future cognitive decline j zhang, c stonnington, q li, j shi, rj bauer, ba gutman, k chen. Multivariate statistics consisting of multivariate tensorbased morphometry mtbm and radial distance were computed for surface deformation analysis. Prior to running tbm in brainsuite statistics toolbox bss, cortical surface extraction and surfacevolume registration need to be run on your subject data. Tensorbased morphometry tbm studies encode the anatomical information in spatial deformations which are locally characterized by jacobian matrices. A matlab user interface for the statistically assisted. Medical imaging, ieee transactions on 27, 129141 2008. In our experiments, we compared ventricular surface models extracted from 3d brain mri scans of 11 hivaids individuals and 8 matched control subjects, using data previously examined in thompson et al. Morphometrics with spm12 john ashburner wellcome trust centre for neuroimaging, 12 queen square, london, uk. Here we developed a new method, called multivariate tensorbased surface morphometry tbm, and applied it to study lateral ventricular surface differences. Generalized tensorbased morphometry of hivaids using multivariate statistics on deformation tensors natasha lepore, caroline brun, yiyu chou, mingchang chiang, rebecca a. Our surface multivariate tensorbased morphometry mtbm statistics considered a new family of metrics, the logeuclidean metrics arsigny et al.
In contrast, deformationbased morphometry dbm and tensorbased morphometry tbm yield more global measures of structural differences 5, 3, 24, 26, 65, 75. Tensorbased morphometry tbm is a neuroimaging method to assess regional differences in brain structure based on the jacobian determinant of the. Qingyang li, tao yang, liang zhan, derrek paul hibar, neda jahanshad, yalin wang, jieping ye, paul m. Current methods perform voxelwise statistical analysis on some features, such as the jacobian determinant or the cauchygreen deformation tensor, which are not complete descriptors of the local deformation. Multiatlas tensorbased morphometry and its application to a. Motivation imaging data statistical methods to look for regional effects tissue differences between groups or over time vbm, tbm voxeltensorbased morphometry pet positron emmission tomography, fmri functional mri determine activation in the brain due to thought, stimulus or task. Combining thickness information with surface tensorbased. Multivariate statistics are then applied to the parameters describing the estimated nonlinear deformations that ensue. Multivariate tensorbased subcortical morphometry system. Here we developed a new method, called multivariate tensorbased surface morphometry tbm, and applied it to study. Brain morphometry is a subfield of both morphometry and the brain sciences, concerned with the measurement of brain structures and changes thereof during development, aging, learning, disease and evolution. Multivariate statistics of the jacobian matrices in tensor based morphometry and their application to hivaids.
Shape analysis with multivariate tensorbased morphometry and holomorphic differentials. Multivariate tensorbased morphometry study of the lateral ventricular surface in hivaids. Tensorbased morphometry tbm is introduced as a method of identifying regional structural di erences from the gradients of deformations elds. Statistical analysis for longitudinal mr imaging of dementia. Biography research publications software talksteaching contact. Shape analysis with multivariate tensorbased morphometry. The dataset is named usc tensorbased morphometry versions 2. Thompson phd, natasha lepor e phd3 1 school of computing, informatics, and decision systems engineering, arizona state university, tempe, az 85281, usa 2 dept of radiology, childrens hospital. Tensorbased morphometry tbm is an increasingly popular method for group analysis of brain mri data. Generalized tensorbased morphometry of hivaids using multivariate statistics on deformation tensors. In ieee international symposium on biomedical imaging. Faculty programs in biomedical and biological science. Voxelbased morphometry diffeomorphic registration tensorbased morphometry. An advanced white matter tract analysis in frontotemporal dementia and earlyonset alzheimers disease brain imaging behav.
Deformationvoxelbased morphometry brain research imaging. Splatt is an open source software package for highperformance sparse tensor factorization. Research is carried out into the statistical theory of permutation testing for application to multivariate general linear models, and is then used to build software for the analysis of multivariate deformation and tensorbased morphometry data, efficiently correcting for the multiple comparison problem inherent in voxelwise analysis of images. Applying tensorbased morphometry to parametric surfaces. Abstract this paper investigates the performance of a new multivariate method for tensorbased morphometry tbm. Rooted in the riemannian geometry, conformal geometry and hyperbolic geometry, a series of algorithms, including multivariate tensorbased morphometry, surface conformal parameterization, volumetric heat kernel shape descriptor, hyperbolic wasserstein distance, have been developed and applied to human brain mapping research problems relating to. Brain morphometry encyclopedia article citizendium. Human brain mapping with conformal geometry and multivariate tensorbased morphometry jie shi1, paul m. Tensorbased morphometry data generated by the thompson lab loni is available from the download section of the adni archive. For such surfacebased features, the feature dimension is usually much larger than the number of subjects. Surface multivariate tensorbased morphometry on premature neonates. Multivariate tensorbased ventricular morphometry system.
Thompson phd, natasha lepor e phd3 1 school of computing, informatics, and decision systems engineering, arizona state university, tempe, az 85281, usa 2 dept of radiology, childrens hospital of. A persistent homologybased wholebrain network measure system. Using hotellings t 2 test, we found significant morphological deformation in apoe e4 carriers relative to. View in pubmed an advanced white matter tract analysis in frontotemporal dementia and earlyonset alzheimers disease brain imaging behav. Unified voxel and tensorbased morphometry uvtbm using.
Updated tensorbased morphometry data available adni. We apply multivariate tensorbased morphometry to study lateral ventricular surface abnormalities associated with hivaids. We use holomorphic oneforms to obtain a conformal parameterization of ventricular geometry, and to register lateral ventricular surfaces across subjects. Jtj12 application to hivaids we are going to demonstrate. Multivariate statistics of the jacobian matrices in tensor. I frequently offer help on the mailing lists for spm and fsl, have helped to edit parts of the spm wikibook, and have contributed to cmics internal wiki. It has extensive functionality for tensor polynomial simplification including multi. Statistics on riemannian manifolds are developed that exploit the full information in deformation tensor fields. Generalized tensorbased morphometry tbm for the analysis of brain mri and dti. Multiresembalance multitarget lowrank coding mmlc 7. The main steps in the analysis consist of a nonlinear registration to align each individual scan to a common space, and a subsequent statistical analysis to determine morphometric differences, or difference in fiber structure between groups.
Applying sparse coding to surface multivariate tensorbased morphometry to predict future cognitive decline. Since autopsylike dissection is generally impossible on living brains, brain morphometry starts with noninvasive neuroimaging data, typically obtained from magnetic resonance imaging or. Deformationbased and tensorbased morphometry we will use deformationbased and tensorbased morphometry in reference to methods for studying. A pilot study yalin wang phd 1, ashok panigrahy md 2. Jd represents the slope of volumeage curves at the voxel level between two time points, which provides information on.
Introduction the human brain exhibits one of the most complex networks. Introductory concepts for voxelbased statistical analysis. Generalized tensorbased morphometry of hivaids using. In this paper, we introduce theories and algorithms in con.
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