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Title: Tracking the aortic lumen geometry by optimizing the 3D orientation of its cross-sections
Authors: Alvarez, Luis 
Trujillo, Agustín 
Cuenca Hernández, Carmelo 
González Sánchez, Esther 
Esclarín, Julio 
Gomez, Luis 
Mazorra, Luis 
Alemán-Flores, Miguel 
Tahoces, P. G.
Carreira-Villamor, José Martín
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
32 Ciencias médicas
120601 Construcción de algoritmos
120326 Simulación
120602 Ecuaciones diferenciales
Keywords: Aorta
Ellipse tracking
Issue Date: 2017
Publisher: Springer
Project: Nuevos Modelos Matemáticos Para la Segmentación y Clasificación en Imágenes 
Journal: Lecture Notes in Computer Science 
Conference: 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, (MICCAI 2017) 
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.
ISBN: 978-3-319-66184-1
ISSN: 0302-9743
DOI: 10.1007/978-3-319-66185-8_20
Source: Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017. MICCAI 2017. Lecture Notes in Computer Science, v. 10434 LNCS, p. 174-181
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