Abstract
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.
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Franchini, E., Morigi, S., Sgallari, F. (2009). Composed Segmentation of Tubular Structures by an Anisotropic PDE Model. In: Tai, XC., Mørken, K., Lysaker, M., Lie, KA. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2009. Lecture Notes in Computer Science, vol 5567. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02256-2_7
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DOI: https://doi.org/10.1007/978-3-642-02256-2_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02255-5
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