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Surface Foliation Based Brain Morphometry Analysis

  • Chengfeng Wen
  • Na Lei
  • Ming MaEmail author
  • Xin Qi
  • Wen Zhang
  • Yalin Wang
  • Xianfeng Gu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11846)

Abstract

Brain morphometry plays a fundamental role in neuroimaging research. In this work, we propose a novel method for brain surface morphometry analysis based on surface foliation theory. Given brain cortical surfaces with automatically extracted landmark curves, we first construct finite foliations on surfaces. A set of admissible curves and a height parameter for each loop are provided by users. The admissible curves cut the surface into a set of pairs of pants. A pants decomposition graph is then constructed. Strebel differential is obtained by computing a unique harmonic map from surface to pants decomposition graph. The critical trajectories of Strebel differential decompose the surface into topological cylinders. After conformally mapping those topological cylinders to standard cylinders, parameters of standard cylinders (height, circumference) are intrinsic geometric features of the original cortical surfaces and thus can be used for morphometry analysis purpose. In this work, we propose a set of novel surface features. To the best of our knowledge, this is the first work to make use of surface foliation theory for brain morphometry analysis. The features we computed are intrinsic and informative. The proposed method is rigorous, geometric, and automatic. Experimental results on classifying brain cortical surfaces between patients with Alzheimer’s disease and healthy control subjects demonstrate the efficiency and efficacy of our method.

Keywords

Brain morphometry Shape classification Surface foliation Alzheimer disease 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Chengfeng Wen
    • 1
  • Na Lei
    • 2
  • Ming Ma
    • 1
    Email author
  • Xin Qi
    • 1
  • Wen Zhang
    • 3
  • Yalin Wang
    • 3
  • Xianfeng Gu
    • 1
  1. 1.Department of Computer ScienceStony Brook UniversityStony BrookUSA
  2. 2.School of Software and TechnologyDalian University of TechnologyDalianChina
  3. 3.School of Computing, Informatics, and Decision Systems EngineeringArizona State UniversityTempeUSA

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