title: Automated diffusion tensor tractography: implementation and comparison to user-driven tractography.
abstract: OBJECTIVE
  Diffusion tensor tractography offers a unique perspective of white matter anatomy, but proper delineation of white matter tracts of interest generally requires the active involvement of an expert neuroanatomist. The investigators describe the implementation of an automated tractographic method requiring no user input and compare its results to those from user-driven tractography.
  
  
  METHODS
  Fourteen healthy volunteers underwent diffusion tensor imaging at 3 T. Images were registered to a standard template, and predefined seed regions containing tract termini were transformed into subject space for use in unsupervised probabilistic tractography. The output was compared to the results of user-driven tractography performed on the same subjects.
  
  
  RESULTS
  After the selection of suitable smoothing kernels and thresholds, the results of automated tractography closely approximated those of user-driven tractography. The main bodies of the cingulum, inferior fronto-occipital fasciculus, and inferior longitudinal fasciculus were depicted equally well by both methods. Discrepancies mainly arose at the periphery of these tracts, where anatomic uncertainty tends to be greatest.
  
  
  CONCLUSIONS
  Automated tractography can be used to depict white matter anatomy without need for user intervention, particularly if the main body of the tract is of greatest interest.
authors.affiliation: Division of Neuroradiology, University of Pennsylvania, One Silverstein, 3400 Spruce Street, Philadelphia, PA 19104, USA. paolo.nucifora@uphs.upenn.edu
authors.forename: Paolo G P
authors.initials: PG
authors.lastname: Nucifora
authors.forename: Xiaoying
authors.initials: X
authors.lastname: Wu
authors.forename: Elias R
authors.initials: ER
authors.lastname: Melhem
authors.forename: Raquel E
authors.initials: RE
authors.lastname: Gur
authors.forename: Ruben C
authors.initials: RC
authors.lastname: Gur
authors.forename: Ragini
authors.initials: R
authors.lastname: Verma
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity