Christian Brechbühler

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This paper presents procedures for the explicit parametric representation and global description of surfaces of simply connected 3-D objects. The novel techniques overcome severe limitations of earlier methods (restriction to star-shaped objects 1], constraints on positioning and shape of cross-sections 2, 3], and nonhomogeneous distribution of parameter(More)
This paper presents a new approach to the correction of intensity inhomogeneities in magnetic resonance imaging (MRI) that significantly improves intensity-based tissue segmentation. The distortion of the image brightness values by a low-frequency bias field impedes visual inspection and segmentation. The new correction method called parametric bias field(More)
This paper describes a new model-based segmentation technique combining desirable properties of physical models (snakes, 2]), shape representation by Fourier parametrization (Fourier snakes, 12]), and modelling of natural shape variability (eigenmodes, 7, 10]). Flexible shape models are represented by a parameter vector describing the mean contour and by a(More)
— Shape analysis has become of increasing interest to the neuroimaging community due to its potential to precisely locate morphological changes between healthy and pathological structures. This manuscript presents a comprehensive set of tools for the computation of 3D structural statistical shape analysis. It has been applied in several studies on brain(More)
Virtual reality based surgical simulator systems offer a very elegant solution to the development of endoscopic surgical trainers. While the graphical performance of commercial systems already makes PC-based simulators viable, the real-time simulation of soft tissue deformation is still the major obstacle in developing simulators for soft-tissue surgery.(More)
A novel bias correction technique is proposed based on the estimation of the parameters of a polynomial bias eld directly from image data. The procedure overcomes diiculties known from homomor-phic ltering or from techniques assuming an initial presegmented image. The only parameters are a set of expected class means and the standard deviation. Applications(More)
A procedure for the parameterization of surface meshes of objects with spherical topology is presented. The generation of such a parameterization has been formulated and solved as a large constrained optimization problem by Brechbühler, but the convergence of this algorithm becomes unstable for object meshes consisting of several thousand vertices. We(More)