Shape transformation using variational implicit functions
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Convexity rule for shape decomposition based on discrete contour evolution
Computer Vision and Image Understanding
Reconstruction and representation of 3D objects with radial basis functions
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Landmark-Based Image Analysis: Using Geometric and Intensity Models
Landmark-Based Image Analysis: Using Geometric and Intensity Models
Modelling with implicit surfaces that interpolate
ACM Transactions on Graphics (TOG)
Efficient Semiautomatic Segmentation of 3D Objects in Medical Images
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Implicit Surfaces that Interpolate
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
Random Walks for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIGGRAPH '05 ACM SIGGRAPH 2005 Courses
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We present a fast and interactive segmentation method for medical images that allows a smooth reconstruction of an object's surface from a set of user drawn, three-dimensional, planar contours that can be arbitrarily oriented. Our algorithm uses an interpolation based on variational implicit functions. Because variational interpolation is computationally expensive, we show how to speed up the algorithm to achieve an interactive calculation time while preserving the overall segmentation quality. The performance improvements are based on a quality preserving reduction of the number of contour points and a fast voxelization strategy for the resulting implicit function. A huge speedup is achieved by the parallelization of the algorithms, utilizing modern 64-bit multi-core CPUs. Finally, we discuss how to make the interpolation algorithm more robust to selfintersecting and reduced contours.