Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

System for Integrated Neuroimaging Analysis and Processing of Structure

System for Integrated Neuroimaging Analysis and Processing of Structure Mapping brain structure in relation to neurological development, function, plasticity, and disease is widely considered to be one of the most essential challenges for opening new lines of neuro-scientific inquiry. Recent developments with MRI analysis of structural connectivity, anatomical brain segmentation, cortical surface parcellation, and functional imaging have yielded fantastic advances in our ability to probe the neurological structure-function relationship in vivo. To date, the image analysis efforts in each of these areas have typically focused on a single modality. Here, we extend the cortical reconstruction using implicit surface evolution (CRUISE) methodology to perform efficient, consistent, and topologically correct analyses in a natively multi-parametric manner. This effort combines and extends state-of-the-art techniques to simultaneously consider and analyze structural and diffusion information alongside quantitative and functional imaging data. Robust and consistent estimates of the cortical surface extraction, cortical labeling, diffusion-inferred contrasts, diffusion tractography, and subcortical parcellation are demonstrated in a scan-rescan paradigm. Accompanying this demonstration, we present a fully automated software system complete with validation data. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Neuroinformatics Springer Journals

System for Integrated Neuroimaging Analysis and Processing of Structure

Download PDF
13 pages

Loading next page...
 
/lp/springer-journals/system-for-integrated-neuroimaging-analysis-and-processing-of-CT9Rp8ndsi
Publisher
Springer Journals
Copyright
Copyright © 2012 by Springer Science+Business Media, LLC
Subject
Biomedicine; Neurosciences; Bioinformatics; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Neurology
ISSN
1539-2791
eISSN
1559-0089
DOI
10.1007/s12021-012-9159-9
pmid
22932976
Publisher site
See Article on Publisher Site

Abstract

Mapping brain structure in relation to neurological development, function, plasticity, and disease is widely considered to be one of the most essential challenges for opening new lines of neuro-scientific inquiry. Recent developments with MRI analysis of structural connectivity, anatomical brain segmentation, cortical surface parcellation, and functional imaging have yielded fantastic advances in our ability to probe the neurological structure-function relationship in vivo. To date, the image analysis efforts in each of these areas have typically focused on a single modality. Here, we extend the cortical reconstruction using implicit surface evolution (CRUISE) methodology to perform efficient, consistent, and topologically correct analyses in a natively multi-parametric manner. This effort combines and extends state-of-the-art techniques to simultaneously consider and analyze structural and diffusion information alongside quantitative and functional imaging data. Robust and consistent estimates of the cortical surface extraction, cortical labeling, diffusion-inferred contrasts, diffusion tractography, and subcortical parcellation are demonstrated in a scan-rescan paradigm. Accompanying this demonstration, we present a fully automated software system complete with validation data.

Journal

Neuroinformatics – Springer Journals

Published: Aug 30, 2012

References

  • How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging
    Andersson, JLR; Skare, S; Ashburner, J
  • Voxel-based morphometry–the methods
    Ashburner, J; Friston, KJ
  • Topology-preserving tissue classification of magnetic resonance brain images
    Bazin, PL; Pham, DL
  • Topology correction of segmented medical images using a fast marching algorithm
    Bazin, PL; Pham, DL
  • Homeomorphic brain image segmentation with topological and statistical atlases
    Bazin, P-L; Pham, DL
  • Direct segmentation of the major white matter tracts in diffusion tensor images
    Bazin, PL
  • Computing large deformation metric mappings via geodesic flows of diffeomorphisms
    Beg, F; Miller, M; Trouve, A; Younes
  • Simple paradigm for extra-cerebral tissue removal: algorithm and analysis
    Carass, A
  • BrainVISA: Software platform for visualization and analysis of multi-modality brain data
    Cointepas, Y
  • Cortical surface-based analysis. I. Segmentation and surface reconstruction
    Dale, AM; Fischl, B; Sereno, MI
  • An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest
    Desikan, RS
  • Active fibers: Matching deformable tract templates to diffusion tensor images
    Eckstein, I
  • Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system
    Fischl, B; Sereno, MI; Dale, AM
  • A topology preserving level set method for geometric deformable models
    Han, X; Xu, C; Prince, JL
  • CRUISE: cortical reconstruction using implicit surface evolution
    Han, X
  • Correction for geometric distortion in echo planar images from B0 field variations
    Jezzard, P; Balaban, RS
  • Characterization and correction for Eddy current artifacts in echo planar diffusion imaging
    Jezzard, P; Barnett, AS; Pierpaoli, C
  • Studying connections in the living human brain with diffusion MRI
    Jones, DK
  • Surface shape and curvature scales
    Koenderink, JJ; Doorn, AJ
  • Effects of diffusion weighting schemes on the reproducibility of DTI-derived fractional anisotropy, mean diffusivity, and principal eigenvector measurements at 1.5T
    Landman, BA
  • Multi-parametric neuroimaging reproducibility: A 3T resource study
    Landman, B
  • Atlas-based segmentation of white matter tracts of the human brain using diffusion tensor tractography and comparison with classical dissection
    Lawes, INC
  • DTI segmentation by statistical surface evolution
    Lenglet, C; Rousson, M; Deriche, R
  • The Java Image Science Toolkit (JIST) for rapid prototyping and publishing of neuroimaging software
    Lucas, BC
  • Automated 3-D extraction of inner and outer surfaces of cerebral cortex from MRI
    MacDonald, D
  • Multimodality image registration by maximization of mutual information
    Maes, F
  • From 3D magnetic resonance images to structural representations of the cortex topography using topology preserving deformations
    Mangin, J-F
  • Open Access Series of Imaging Studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults
    Marcus, D
  • Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging
    Mori, S
  • Ways toward an early diagnosis in Alzheimer’s disease: the Alzheimer’s Disease Neuroimaging Initiative (ADNI)
    Mueller, SG
  • Adaptive fuzzy segmentation of magnetic resonance images
    Pham, DL; Prince, JL
  • Automatic recognition of cortical sulci of the human brain using a congregation of neural networks
    Riviere, D
  • The adaptive bases algorithm for intensity-based nonrigid image registration
    Rohde, GK; Aldroubi, A; Dawant, BM
  • Comprehensive approach for correction of motion and distortion in diffusion-weighted MRI
    Rohde, GK
  • Level Set Methods and Fast Marching Methods. Vol. second ed
    Sethian, JA
  • BrainSuite: An automated corticalsurface identification tool. in Lecture Notes in Computer Science. Medical Image Computing and Computer-Assisted Intervention MICCAI
    Shattuck, DW; Leahy, RM
  • Advances in functional and structural MR image analysis and implementation as FSL
    Smith, SM
  • Organization, development and function of complex brain networks
    Sporns, O
  • Longitudinal changes in cortical thickness associated with normal aging
    Thambisetty, M
  • A framework for computational anatomy
    Thompson, PM; Toga, AW
  • Mapping techniques for aligning sulci across multiple brains
    Tosun, D; Rettmann, M; Prince, J
  • An integrated software suite for surface-based analyses of cerebral cortex
    Essen, DC
  • Automated model-based tissue classification of MR images of the brain
    Leemput, K
  • Reproducibility of quantitative tractography methods applied to cerebral white matter
    Wakana, S
  • Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation
    Warfield, SK; Zou, KH; Wells, WM
  • Reconstruction of the human cerebral cortex from magnetic resonance images
    Xu, C
  • Segmentation and measurement of the cortex from 3-D MR images using coupled-surfaces propagation
    Zeng, X