3 July 2001 Local-cost computation for efficient segmentation of 3D objects with live wire
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Abstract
We present an approach for the optimization of the live wire algorithm applied to 3D medical images. Our method restricts the computation of the cost function to relevant areas and considers regionally specific properties of the object boundary. As a consequence, precise contours can be obtained in reduced computation and interaction time. For the calculation of the cost function on the current image slice, the nearest contour on an adjacent slice is taken as reference. The reference contour is divided into local segments and the image pixels are classified into regions with respect to their distance to the contour segments. The size of these regions is controlled by a given maximum distance. Cost function parameters are learned separately from every local contour segment of the reference slice and define the cost function for the respective region on the current slice. We used the local cost computation for the interactive definition of object contours, as well as for the optimization of interpolated contours between user-defined contours. Applied to CT and MR data of the liver, our method showed considerable advantages over the conventional algorithm based on a global cost function, particularly for objects with inhomogeneities or with different surrounding tissue.
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Andrea Schenk, Andrea Schenk, Guido P. M. Prause, Guido P. M. Prause, Heinz-Otto Peitgen, Heinz-Otto Peitgen, } "Local-cost computation for efficient segmentation of 3D objects with live wire", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); doi: 10.1117/12.431015; https://doi.org/10.1117/12.431015
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