Tracking the aortic lumen geometry by optimizing the 3D orientation of its cross-sections

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Abstract

We propose a fast incremental technique to compute the 3D geometry of the aortic lumen from a seed point located inside it. Our approach is based on the optimization of the 3D orientation of the cross-sections of the aorta. The method uses a robust ellipse estimation algorithm and an energy-based optimization technique to automatically track the centerline and the cross sections. In order to perform the optimization, we consider the size and the eccentricity of the ellipse which best fit the contour of the aorta on each cross-sectional plane. The method works directly on the original image and does not require a prior segmentation of the aortic lumen. We present some preliminary results which show the accuracy of the method and its ability to cope with challenging real CT (computed tomography) images of aortic lumens with significant angulations due to severe elongations.

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Alvarez, L., Trujillo, A., Cuenca, C., González, E., Esclarín, J., Gomez, L., … Carreira, J. M. (2017). Tracking the aortic lumen geometry by optimizing the 3D orientation of its cross-sections. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10434 LNCS, pp. 174–181). Springer Verlag. https://doi.org/10.1007/978-3-319-66185-8_20

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