A combined level set/mesh warping algorithm for tracking brain and cerebrospinal fluid evolution in hydrocephalic patients

Jeonghyung Park, Suzanne M. Shontz, Corina S. Drapaca

Research output: Chapter in Book/Report/Conference proceedingChapter

8 Scopus citations

Abstract

Hydrocephalus is a neurological disease which occurs when normal cerebrospinal fluid (CSF) circulation is impeded within the cranial cavity. As a result, the brain ventricles enlarge, and the tissue compresses, causing physical and mental problems. Treatment has been mainly through CSF flow diversion by surgically implanting a CSF shunt in the brain ventricles or by performing an endoscopic third ventriculostomy (ETV). However, the patient response to either treatment continues to be poor. Therefore, there is an urgent need to design better therapy protocols for hydrocephalus. An important step in this direction is the development of predictive computational models of the mechanics of hydrocephalic brains. In this paper, we propose a combined level set/mesh warping algorithm to track the evolution of the ventricles in the hydrocephalic brain. Our combined level set/mesh warping method is successfully used to track the evolution of the brain ventricles in two hydrocephalic patients.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computational Vision and Biomechanics
PublisherSpringer Netherlands
Pages107-141
Number of pages35
DOIs
StatePublished - Jan 1 2013

Publication series

NameLecture Notes in Computational Vision and Biomechanics
Volume3
ISSN (Print)2212-9391
ISSN (Electronic)2212-9413

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All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Artificial Intelligence

Cite this

Park, J., Shontz, S. M., & Drapaca, C. S. (2013). A combined level set/mesh warping algorithm for tracking brain and cerebrospinal fluid evolution in hydrocephalic patients. In Lecture Notes in Computational Vision and Biomechanics (pp. 107-141). (Lecture Notes in Computational Vision and Biomechanics; Vol. 3). Springer Netherlands. https://doi.org/10.1007/978-94-007-4255-0_7