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EN
In image processing, models are used to improve robustness of algorithms by introducing a priori knowledge. Deformable models, frequently used in the field of medical images, are described by means of energy functionals with data attachment terms and regularising terms. The regularising terms express constraints relating to the expected shapes. The expected shape of a blood vessel segment in 3D images obtained by Magnetic Resonance Imaging or by helicoidal Computed Tomography is often implicitly described by a generalised cylinder model, i.e. an association of an axis (vessel centreline) and a surface (vessel boundary). In this context, the data attachment terms involve, for candidate points, a measure of the likelihood of being located on the centreline or on the boundary. Such a measure can use models reflecting low-level local photometrical properties of the brightness patterns. This presentation will give an overview of the recently used models and will be illustrated by the authors' contribution.
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