Adaptive surface data compression

Surgical Planning Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA
Signal Processing (Impact Factor: 2.21). 06/1997; 59(2):211-220. DOI: 10.1016/S0165-1684(97)00047-9


Three-dimensional (3D) visualization techniques are becoming an important tool for medical applications. Computer-generated 3D reconstructions of the human skull are used to build stereolithographic models, which can be used to simulate surgery or to create individual implants. Anatomy-based 3D models are used to simulate the physical behaviour of human organs. These 3D models are usually displayed by a polygonal description of their surface, which requires hundreds of thousands of polygons. For interactive applications this large number of polygons is a major obstacle. We have improved an adaptive compression algorithm that significantly reduces the number of triangles required to model complex objects without losing visible detail and have implemented it in our surgery simulation system. We present this algorithm using human skull and skin data and describe the efficiency of this new approach.

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