29 April 2005 Characterization of cerebral aneurysms using 3D moment invariants
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Abstract
The rupture mechanism of intracranial aneurysms is still not fully understood. Although the size of the aneurysm is the shape index most commonly used to predict rupture, some controversy still exists about its adequateness as an aneurysm rupture predictor. In this work, an automatic method to geometrically characterize the shape of cerebral saccular aneurysms using 3D moment invariants is proposed. Geometric moments are efficiently computed via application of the Divergence Theorem over the aneurysm surface using a non-structured mesh. 3D models of the aneurysm and its connected parent vessels have been reconstructed from segmentations of both 3DRA and CTA images. Two alternative approaches have been used for segmentation, the first one based on isosurface deformable models, and the second one based on the level set method. Several experiments were also conducted to both assess the influence of pre-processing steps in the stability of the aneurysm shape descriptors, and to know the robustness of the proposed method. Moment invariants have proved to be a robust technique while providing a reliable way to discriminate between ruptured and unruptured aneurysms (Sensitivity=0.83, Specificity=0.74) on a data set containing 55 aneurysms. Further investigation over larger databases is necessary to establish their adequateness as reliable predictors of rupture risk.
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Raul Daniel Millan, Raul Daniel Millan, Monica Hernandez, Monica Hernandez, Daniel Gallardo, Daniel Gallardo, Juan Raul Cebral, Juan Raul Cebral, Christopher Putman, Christopher Putman, Laura Dempere-Marco, Laura Dempere-Marco, Alejandro Federico Frangi, Alejandro Federico Frangi, } "Characterization of cerebral aneurysms using 3D moment invariants", Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.595881; https://doi.org/10.1117/12.595881
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