Deformable model reconstruction of the subarachnoid space

Jeffrey Glaister, Muhan Shao, Xiang Li, Aaron Carass, Snehashis Roy, Ari M. Blitz, Jerry L. Prince, Lotta M. Ellingsen

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The subarachnoid space is a layer in the meninges that surrounds the brain and is filled with trabeculae and cerebrospinal fluid. Quantifying the volume and thickness of the subarachnoid space is of interest in order to study the pathogenesis of neurodegenerative diseases and compare with healthy subjects. We present an automatic method to reconstruct the subarachnoid space with subvoxel accuracy using a nested deformable model. The method initializes the deformable model using the convex hull of the union of the outer surfaces of the cerebrum, cerebellum and brainstem. A region force is derived from the subject's T1-weighted and T2-weighted MRI to drive the deformable model to the outer surface of the subarachnoid space. The proposed method is compared to a semi-automatic delineation from the subject's T2-weighted MRI and an existing multi-atlas-based method. A small pilot study comparing the volume and thickness measurements in a set of age-matched subjects with normal pressure hydrocephalus and healthy controls is presented to show the efficacy of the proposed method.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2018
Subtitle of host publicationImage Processing
EditorsElsa D. Angelini, Elsa D. Angelini, Bennett A. Landman
ISBN (Electronic)9781510616370
StatePublished - 2018
EventMedical Imaging 2018: Image Processing - Houston, United States
Duration: Feb 11 2018Feb 13 2018

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


OtherMedical Imaging 2018: Image Processing
Country/TerritoryUnited States


  • MRI
  • deformable models
  • normal pressure hydrocephalus
  • subarachnoid space

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging


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