Algorithm for blood-vessel segmentation in 3D images based on a right generalized cylinder model: Application to carotid arteries

Leonardo Flórez Valencia, Jacques Azencot, MacIej Orkisz

Producción: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

7 Citas (Scopus)

Resumen

The arterial lumen is modeled by a spatially continuous right generalized cylinder with piece-wise constant parameters. The method is the identifies the parameters of each cylinder piece from a series of planar contours extracted along an approximate axis of the artery. This curve is defined by a minimal path between the artery end-points. The contours are extracted by use of a 2D Fast Marching algorithm. The identification of the axial parameters is based on a geometrical analogy with piece-wise helical curves, while the identification of the surface parameters uses the Fourier series decomposition of the contours. Thus identified parameters are used as observations in a Kalman optimal estimation scheme that manages the spatial consistency from each piece to another. The method was evaluated on 15 datasets from the MICCAI 3D Segmentation in the Clinic Grand Challenge: Carotid Bifurcation Lumen Segmentation and Stenosis Grading ( http://cls2009.bigr.nl/ ). The average Dice similarity score was 71.4.

Idioma originalInglés
Título de la publicación alojadaComputer Vision and Graphics - International Conference, ICCVG 2010, Proceedings
EditorialSpringer Verlag
Páginas27-34
Número de páginas8
EdiciónPART 1
ISBN (versión impresa)3642159095, 9783642159091
DOI
EstadoPublicada - 2010

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NúmeroPART 1
Volumen6374 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

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