Segmentation of the thrombus of giant intracranial aneurysms from CT angiography scans with lattice Boltzmann method

Med Image Anal. 2014 Jan;18(1):1-8. doi: 10.1016/j.media.2013.08.003. Epub 2013 Sep 4.

Abstract

Computed Tomography Angiography (CTA) plays an essential role in the diagnosis, treatment evaluation, and monitoring of cerebral aneurysms. Segmentation of CTA medical images of giant intracranial aneurysms (GIA) provides quantitative measurements of thrombus and aneurysms geometrical characteristics allowing 3D reconstruction. In fact, GIA demonstrated neuroradiological features and propensity of partial or total spontaneous intra-aneurysmal thrombosis generating a thrombus. Despite intensive researches on medical image segmentation, aneurysm (Lumen, Thrombus, and Parent Blood Vessels) segmentation remains as a difficult problem that has not been yet resolved. In this paper, we proposed a Lattice Boltzmann Geodesic Active Contour Method (LBGM) for aneurysm segmentation in CTA images in order to estimate both the volumes of the thrombus and the aneurysm. Although the noise in the CTA images is very strong and the edges of the thrombus are not so different than the surrounding tissues, the aneurysms are segmented effectively. Based on these results, a method using a dome-neck aspect ratio (AR) parameter for the evaluation of the Spontaneous Thrombosis (ST) phenomena demonstrates the promising potentiality of this LBGM for clinical applications.

Keywords: Anisotropic diffusion; Computed tomography angiography; Geodesic active contour; Giant intracranial aneurysm; Lattice Boltzmann method.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Algorithms
  • Cerebral Angiography / methods*
  • Female
  • Humans
  • Imaging, Three-Dimensional / methods*
  • Intracranial Aneurysm / complications
  • Intracranial Aneurysm / diagnostic imaging*
  • Intracranial Thrombosis / diagnostic imaging*
  • Intracranial Thrombosis / etiology
  • Male
  • Middle Aged
  • Pattern Recognition, Automated / methods*
  • Radiographic Image Interpretation, Computer-Assisted / methods
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Subtraction Technique*
  • Tomography, X-Ray Computed / methods*