3D Object Reconstruction from Parallel Cross-Sections
ICCVG 2008 Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers
Static methods for object reconstruction overview: for medical diagnosis
Annales UMCS, Informatica
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A method for reconstructing 3D models from cross- sectional signals is presented. This is specifically useful for low resolution images (E.G. seismic, ultrasound); the method is not voxel based, and is faster and uses less memory than methods that are. The algorithm starts with preprocessing the images by thresholding, segmenting, contour finding, point sampling and then triangulating. The main objective of this algorithm was to produce the smoothest possible model for branching bodies taking into consideration that the slices might be far apart in reality and consequently a novel branching/interpolation technique was used that proved superior to existing methods for this purpose. At the same time it did not need involvement of the user for objects within defined classes. Seismic simulations and CT data have been used to test the algorithm. We succeeded in reconstructing the tomb of Tut Ankh Amen (an Egyptian Pharaoh) from simulated seismic data.