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Interactive exploration of a 3D intracranial aneurysm wall model extracted from histologic slices.
- Source :
- International Journal of Computer Assisted Radiology & Surgery; Jan2020, Vol. 15 Issue 1, p99-107, 9p
- Publication Year :
- 2020
-
Abstract
- Purpose: Currently no detailed in vivo imaging of the intracranial vessel wall exists. Ex vivo histologic images can provide information about the intracranial aneurysm (IA) wall composition that is useful for the understanding of IA development and rupture risk. For a 3D analysis, the 2D histologic slices must be incorporated in a 3D model which can be used for a spatial evaluation of the IA's morphology, including analysis of the IA neck. Methods: In 2D images of histologic slices, different wall layers were manually segmented and a 3D model was generated. The nuclei were automatically detected and classified as round or elongated, and a neural network-based wall type classification was performed. The information was combined in a software prototype visualization providing a unique view of the wall characteristics of an IA and allowing interactive exploration. Furthermore, the heterogeneity (as variance of the wall thickness) of the wall was evaluated. Result: A 3D model correctly representing the histologic data was reconstructed. The visualization integrating wall information was perceived as useful by a medical expert. The classification produces a plausible result. Conclusion: The usage of histologic images allows to create a 3D model with new information about the aneurysm wall. The model provides information about the wall thickness, its heterogeneity and, when performed on cadaveric samples, includes information about the transition between IA neck and sac. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 18616410
- Volume :
- 15
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- International Journal of Computer Assisted Radiology & Surgery
- Publication Type :
- Academic Journal
- Accession number :
- 141098794
- Full Text :
- https://doi.org/10.1007/s11548-019-02083-0