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EnglishIn this work we introduce the composed segmentation (C- segmentation), that is a priori composition of sources to obtain a sin- gle one segmentation result according to speci¯c Boolean operations. 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 Di®erential Equation (PDE)-based di®usion model derived from a minimal volume- like variational formulation. The gradient °ow for this functional leads to a nonlinear curvature motion model. An anisotropic variant is provided which includes a di®usion 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.
| Titolo: | Composed Segmentation of Tubular Structures by an Anisotropic PDE Model | |
| Autore/i: | MORIGI, SERENA; SGALLARI, FIORELLA; FRANCHINI, ELENA | |
| Autore/i Unibo: | ||
| Anno: | 2009 | |
| Titolo del libro: | Lecture Notes in Computer Science: Scale Space and Variational Methods in Computer Vision | |
| Pagina iniziale: | 75 | |
| Pagina finale: | 86 | |
| Abstract: | In this work we introduce the composed segmentation (C- segmentation), that is a priori composition of sources to obtain a sin- gle one segmentation result according to speci¯c Boolean operations. 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 Di®erential Equation (PDE)-based di®usion model derived from a minimal volume- like variational formulation. The gradient °ow for this functional leads to a nonlinear curvature motion model. An anisotropic variant is provided which includes a di®usion 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. | |
| Data prodotto definitivo in UGOV: | 6-mag-2009 | |
| Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |
File in questo prodotto:
http://hdl.handle.net/11585/75940
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