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Related Experiment Video

Updated: May 3, 2026

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
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Image segmentation methods for intracranial aneurysm haemodynamic research.

Yuka Sen1, Yi Qian1, Alberto Avolio1

  • 1The Australian School of Advanced Medicine, Macquarie University, 2 Technology Place, Sydney, NSW 2109, Australia.

Journal of Biomechanics
|January 28, 2014
PubMed
Summary
This summary is machine-generated.

Accurate segmentation of intracranial aneurysms is crucial for patient-specific hemodynamic simulations. Comparing three methods revealed significant differences in results, highlighting the need for validation in clinical applications.

Keywords:
BrainHaemodynamicsIntracranial aneurysmLevel setMedical image segmentationRegion growing threshold

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Area of Science:

  • Biomedical Engineering
  • Medical Imaging Analysis
  • Computational Fluid Dynamics

Background:

  • Patient-specific hemodynamic technology relies on accurate medical image segmentation.
  • Intracranial aneurysm geometry and volume vary significantly with segmentation methods.
  • Validated segmentation is essential for reliable patient-specific hemodynamic analysis.

Purpose of the Study:

  • To compare three distinct segmentation methods for intracranial aneurysms.
  • To evaluate the impact of segmentation on patient-specific hemodynamic simulations.
  • To assess the necessity of validating segmentation techniques.

Main Methods:

  • Compared Region Growing Threshold (RGT), Chan-Vese (CV), and Threshold-Based Level Set (TLS) segmentation methods.
  • Assessed 45 patient-specific intracranial aneurysm cases across three anatomical locations.
  • Evaluated results using volume difference (VD), local geometry, and hemodynamic simulation metrics (energy loss, Wall Shear Stress).

Main Results:

  • Average volume difference (VD) across methods was 9.3%.
  • Significant differences observed in hemodynamic parameters: average energy loss (23.2%), Wall Shear Stress (WSS) (24.0% highest, 126.4% lowest).
  • Lowest WSS values were highly dependent on aneurysm surface geometry.

Conclusions:

  • Segmentation method choice critically impacts patient-specific hemodynamic simulation outcomes.
  • Significant variations in energy loss and Wall Shear Stress underscore the need for careful method selection.
  • Validation of segmentation techniques is essential for accurate cerebrovascular hemodynamic analysis.