Computational geometry: an introduction
Computational geometry: an introduction
Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Direct Least Square Fitting of Ellipses
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised cell nucleus segmentation with active contours
Signal Processing - Special issue on deformable models and techniques for image and signal processing
General Object Reconstruction Based on Simplex Meshes
International Journal of Computer Vision
| Hi-index | 0.00 |
Spherical object reconstruction is of great importance, especially in the field of cell biology, since cells as well as cell nuclei mostly have the shape of a deformed sphere. Fast, reliable and precise procedure is needed for automatic measuring of topographical parameters of the large number of cells or cell nuclei. This paper presents a new method for spherical object reconstruction. The method springs from Delingette general object reconstruction algorithm which is based on the deformation of simplex meshes. However, the unknown surface is searched only within the subclass of simplex meshes, which have the shape of a star. Star-shaped simplex meshes are suitable for modelling of spherical or ellipsoidal objects. In our approach, the law of motion was altered so that it preserves the star-shape during deformation. The proposed method is easier than the general method and therefore faster. In addition, it uses more computationally stable expressions than a method strictly implemented according to Delingette's paper. It is also shown how to partly avoid the occasional instability of the Delingette method. The accuracy of both methods is comparable. The star-shaped method achieves a stable state more often.