A new method for reconstructing 3-D shape from CT images is proposed in this paper. This approach recovers the original appearance of the organ by applying an evolutionary process to generate the interpolated contours for filling gaps between adjacent slices. It utilizes global shape information and prevents complicated matching with local features. It is powerful in handling CT images with large or unequal distance between slices. The morphological operations with suitable 3-D structuring elements, which can be implemented with parallel hardware, are used to suppress small fluctuations on the shape. Our new method provides a better visualization tool in clinical CT applications.