Automatic measurement of midline shift on deformed brains using multiresolution binary level set method and Hough transform

Furen Xiao, I. Jen Chiang, Jau Min Wong, Yi Hsin Tsai, Ke Chun Huang, Chun Chih Liao

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

Midline shift (MLS) is an important quantitative feature clinicians use to evaluate the severity of brain compression by various pathologies. The midline consists of many anatomical structures including the septum pellucidum (SP), a thin membrane between the frontal horns (FH) of the lateral ventricles. We proposed a procedure that can measure MLS by recognizing the SP within the given CT study. The FH region is selected from all ventricular regions by expert rules and the multiresolution binary level set method. The SP is recognized using Hough transform, weighted by repeated morphological erosion. Our system is tested on images from 80 patients admitted to the neurosurgical intensive care unit. The results are evaluated by human experts. The mean difference between automatic and manual MLS measurements is 0.23±0.52 mm. Our method is robust and can be applied in emergency and routine settings.

Original languageEnglish
Pages (from-to)756-762
Number of pages7
JournalComputers in Biology and Medicine
Volume41
Issue number9
DOIs
Publication statusPublished - Sept 2011

Keywords

  • Brain deformation
  • Computed tomography
  • Hough transform
  • Level set
  • Medical informatics
  • Midline shift
  • Pathological images

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

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