In this work we introduce the composed segmentation (C-segmentation), that is a priori composition of sources to obtain a single one segmentation result according to specific logic combinations. The approach and the segmentation model are general but we apply the C-segmentation technique to the challenging problem of segmenting tubular-like structures. The reconstruction is obtained by continuously deforming an initial distance function following the Partial Differential Equation (PDE)-based diffusion model derived from a minimal volume-like variational formulation. The gradient flow for this functional leads to a nonlinear curvature motion model. An anisotropic variant is provided which includes a diffusion tensor aimed to follow the tube geometry. Numerical examples demonstrate the ability of the proposed method to produce high quality 2D/3D segmentations of complex and eventually incomplete synthetic and real data. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Franchini, E., Morigi, S., & Sgallari, F. (2009). Composed segmentation of tubular structures by an anisotropic PDE model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5567 LNCS, pp. 75–86). https://doi.org/10.1007/978-3-642-02256-2_7
Mendeley helps you to discover research relevant for your work.