Intracranial aneurysm segmentation in 3D CT angiography: method and quantitative validation

Azadeh Firouzian; R. Manniesing; Z. H. Flach; R. Risselada; F. van Kooten; M. C. J. M. Sturkenboom; A. van der Lugt; W. J. Niessen

doi:10.1117/12.843674

12 March 2010 Intracranial aneurysm segmentation in 3D CT angiography: method and quantitative validation

Azadeh Firouzian, R. Manniesing, Z. H. Flach, R. Risselada, F. van Kooten, M. C. J. M. Sturkenboom, A. van der Lugt, W. J. Niessen

Author Affiliations +

Proceedings Volume 7623, Medical Imaging 2010: Image Processing; 76233M (2010) https://doi.org/10.1117/12.843674
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

Accurately quantifying aneurysm shape parameters is of clinical importance, as it is an important factor in choosing the right treatment modality (i.e. coiling or clipping), in predicting rupture risk and operative risk and for pre-surgical planning. The first step in aneurysm quantification is to segment it from other structures that are present in the image. As manual segmentation is a tedious procedure and prone to inter- and intra-observer variability, there is a need for an automated method which is accurate and reproducible. In this paper a novel semi-automated method for segmenting aneurysms in Computed Tomography Angiography (CTA) data based on Geodesic Active Contours is presented and quantitatively evaluated. Three different image features are used to steer the level set to the boundary of the aneurysm, namely intensity, gradient magnitude and variance in intensity. The method requires minimum user interaction, i.e. clicking a single seed point inside the aneurysm which is used to estimate the vessel intensity distribution and to initialize the level set. The results show that the developed method is reproducible, and performs in the range of interobserver variability in terms of accuracy.

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Azadeh Firouzian, R. Manniesing, Z. H. Flach, R. Risselada, F. van Kooten, M. C. J. M. Sturkenboom, A. van der Lugt, and W. J. Niessen "Intracranial aneurysm segmentation in 3D CT angiography: method and quantitative validation", Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76233M (12 March 2010); https://doi.org/10.1117/12.843674

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