Selective Segmentation of 3-D Objects Using Surface Detection and Volume Growing

The segmentation of target objects from three dimensional volume images is an essential step for visualization and volume measurement. In this paper, we present a method to detect the surface of objects by improving the widely used levoy filtering for volume visualization. Using morphological operators we generate completely closed surfaces and selectively segment objects using the volume growing algorithm. The presented method was applied to 3-D artificial sphere images and angiocardiograms. We quantitatively compared this method with the conventional levoy filtering using artificial sphereimages, and the results showed that our method is better in the aspect of voxel errors. The results of visual comparison using angiocardiograms also showed that our method is more accurate. The presented method in this paper is very effective for segmentation of volume data because segmentation, visualization and measurement are frequently used together for 3-D image processing and they can be easily related in our method.