Per Rønsholt Andresen

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From a set of longitudinal three-dimensional scans of the same anatomical structure, we have accurately modeled the temporal shape and size changes using a linear shape model. On a total of 31 computed tomography scans of the mandible from six patients, 14,851 semilandmarks are found automatically using shape features and a new algorithm called(More)
Assume that only partial knowledge about a non-rigid registration is given: certain points, curves or surfaces in one 3D image are known to map to certain points, curves or surfaces in another 3D image. In trying to identify the non-rigid displacement field, we face a generalized aperture problem since along the curves and surfaces, point correspondences(More)
Given a sparse set of feature matches, we want to compute an interpolated dense displacement map. The application may be stereo disparity computation, ow computation, or non-rigid medical registration. Also estimation of missing image data, may be phrased in this framework. Since the features often are very sparse, the interpolation model becomes crucial.(More)
An automated system for registration of tail bleeding in rats using a camera and a user-designed PC-based software program has been developed. The live and processed images are displayed on the screen and are exported together with a text file for later statistical processing of the data allowing calculation of e.g. number of bleeding episodes, bleeding(More)
Deformable template models are a very popular and powerful tool within the eld of image processing and computer vision. This thesis treats this type of models extensively with special focus on handling their common diÆculties, i.e. model parameter selection, initialization and optimization. A proper handling of the common diÆculties is essential for making(More)
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