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PASTA: Pointwise assessment of streamline tractography attributes
Author(s) -
Jones Derek K.,
Travis Adam R.,
Eden Greg,
Pierpaoli Carlo,
Basser Peter J.
Publication year - 2005
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.20484
Subject(s) - tractography , diffusion mri , computer science , pointwise , orientation (vector space) , visualization , white matter , artificial intelligence , segmentation , fractional anisotropy , tensor (intrinsic definition) , pattern recognition (psychology) , computer vision , magnetic resonance imaging , mathematics , radiology , medicine , mathematical analysis , geometry , pure mathematics
Diffusion tensor MRI tractography aims to reconstruct noninvasively the 3D trajectories of white matter fasciculi within the brain, providing neuroscientists and clinicians with a potentially useful tool for mapping brain architecture. While this technique is widely used to visualize white matter pathways, the associated uncertainty in fiber orientation and artifacts have, to date, not been visualized in conjunction with the trajectory data. In this work, the bootstrap method was used to determine the distributions of diffusion indices such as trace and anisotropy, together with the uncertainty in fiber orientation. A novel visualization scheme was developed to encode this information at each point along reconstructed trajectories. By integrating these schemes into a graphical user interface, a new tool which we call PASTA (Pointwise Assessment of Streamline Tractography Attributes) was created to facilitate identification of artifacts in tractography that would otherwise go undetected. Magn Reson Med 53:1462–1467, 2005. Published 2005 Wiley‐Liss, Inc.