20 October 1997 Three-dimensional image modeling based on least squares fitting by using adaptive subdivision of a tetrahedron
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3D image modeling system is highly demanded for automated visual inspection and non-destructive testing. It also can be useful to biomedical research, medical therapy, surgery planning, and simulation of critical surgery. Image processing and image analysis are used to enhance and classify the medical volumetric data. Analyzing medical volumetric data is very difficult. In this paper, we propose a new image modeling method based on least squares fitting by adaptive sub-division of tetrahedron. First, each pixel of the given medical image is enhanced through image processing. next, initial tetrahedral domain is constructed based on sphere criterion with the selected pixels. Finally, refining process is performed through sub-division of tetrahedron based on least squares fitting. User can specify the tolerance. Sub-division is continued until difference between approximation and measured value is less than specified tolerance.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kun Lee, Kun Lee, Oubong Gwun, Oubong Gwun, } "Three-dimensional image modeling based on least squares fitting by using adaptive subdivision of a tetrahedron", Proc. SPIE 3168, Vision Geometry VI, (20 October 1997); doi: 10.1117/12.279667; https://doi.org/10.1117/12.279667


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