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11 May 1994 Nonlinear filtering approach to grayscale interpolation of 3D medical images
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Abstract
Three-dimensional images are now common in radiology. A 3D image is formed by stacking a contiguous sequence of two-dimensional cross-sectional images, or slices. Typically, the spacing between known slices is greater than the spacing between known points on a slice. Many visualization and image-analysis tasks, however, require the 3D image to have equal sample spacing in all directions. To meet this requirement, one applies an interpolation technique to the known 3D image to generate a new uniformly sampled 3D image. We propose a nonlinear-filter-based approach to gray-scale interpolation of 3D images. The method, referred to as column-fitting interpolation, is reminiscent of the maximum-homogeneity filter used for image enhancement. The method is typically more effective than traditional gray-scale interpolation techniques.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
William E. Higgins and Brian E. Ledell "Nonlinear filtering approach to grayscale interpolation of 3D medical images", Proc. SPIE 2167, Medical Imaging 1994: Image Processing, (11 May 1994); https://doi.org/10.1117/12.175062
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