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Supra-Threshold Fiber Cluster Statistics for Data-Driven Whole Brain Tractography Analysis

  • Fan ZhangEmail author
  • Weining Wu
  • Lipeng Ning
  • Gloria McAnulty
  • Deborah Waber
  • Borjan Gagoski
  • Kiera Sarill
  • Hesham M. Hamoda
  • Yang Song
  • Weidong Cai
  • Yogesh Rathi
  • Lauren J. O’Donnell
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10433)

Abstract

This work presents a supra-threshold fiber cluster (STFC) analysis that leverages the whole brain fiber geometry to enhance statistical group difference analysis. The proposed method consists of (1) a study-specific data-driven tractography parcellation to obtain white matter (WM) tract parcels according to the WM anatomy and (2) a nonparametric permutation-based STFC test to identify significant differences between study populations (e.g. disease and healthy). The basic idea of our method is that a WM parcel’s neighborhood (parcels with similar WM anatomy) can support the parcel’s statistical significance when correcting for multiple comparisons. The method is demonstrated by application to a multi-shell diffusion MRI dataset from 59 individuals, including 30 attention deficit hyperactivity disorder (ADHD) patients and 29 healthy controls (HCs). Evaluations are conducted using both synthetic and real data. The results indicate that our STFC method gives greater sensitivity in finding group differences in WM tract parcels compared to several traditional multiple comparison correction methods.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Fan Zhang
    • 1
    Email author
  • Weining Wu
    • 1
    • 2
  • Lipeng Ning
    • 1
  • Gloria McAnulty
    • 3
  • Deborah Waber
    • 3
  • Borjan Gagoski
    • 3
  • Kiera Sarill
    • 3
  • Hesham M. Hamoda
    • 3
  • Yang Song
    • 4
  • Weidong Cai
    • 4
  • Yogesh Rathi
    • 1
  • Lauren J. O’Donnell
    • 1
  1. 1.Brigham and Women’s Hospital, Harvard Medical SchoolBostonUSA
  2. 2.College of Computer Science and TechnologyHarbin Engineering UniversityHarbinChina
  3. 3.Boston Children’s Hospital, Harvard Medical SchoolBostonUSA
  4. 4.School of Information TechnologiesThe University of SydneySydneyAustralia

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