Efficient Semiautomatic Segmentation of 3D Objects in Medical Images

We present a fast and accurate tool for semiautomatic segmentation of volumetric medical images based on the live wire algorithm, shape-based interpolation and a new optimization method. While the user-steered live wire algorithm represents an efficient, precise and reproducible method for interactive segmentation of selected twodimensional images, the shape-based interpolation allows the automatic approximation of contours on slices between user-defined boundaries. The combination of both methods leads to accurate segmentations with significantly reduced user interaction time. Moreover, the subsequent automated optimization of the interpolated object contours results in a better segmentation quality or can be used to extend the distances between user-segmented images and for a further reduction of interaction time. Experiments were carried out on hepatic computer tomographies from three different clinics. The results of the segmentation of liver parenchyma have shown that the user interaction time can be reduced more than 60% by the combination of shape-based interpolation and our optimization method with volume deviations in the magnitude of inter-user differences.