Name
Title | ||
|---|---|---|
Reconstruction of 3D medical images: A nonlinear interpolation technique for reconstruction of 3D medical images |
Abstract | ||
|---|---|---|
Three-dimensional medical images reconstructed from a series of two-dimensional images produced by computerized tomography, magnetic resonance imaging, etc., present a valuable tool for modern medicine. Usually, the interresolution between two cross sections is less than the intraresolution within each cross section. Therefore, interpolations are required to create a 3D visualization. Many techniques, including voxel-based and patch tiling methods, apply linear interpolations between two cross sections. Although those techniques using linear interpolations are economical in computation, they need much cross-sectional data and are unable to enlarge because of aliasing. Hence, the techniques that apply two-dimensional nonlinear interpolation functions among cross sections were proposed. In this paper, we introduce the curvature sampling of the contour of a medical object in a CT (computerized tomography) image. Those sampled contour points are the candidates for the control points of Hermite surfaces between each pair of cross sections. Then, a nearest-neighbor mapping of control points between every two cross sections is used for surface formation. The time complexity of our mapping algorithm is O(m + n), where m and n are the numbers of control points of two cross sections. It is much faster than Kehtarnavaz and De Figueiredo's merge method, whose time complexity is O(n3m2). |
Year | DOI | Venue |
|---|---|---|
1991 | 10.1016/1049-9652(91)90041-H | CVGIP: Graphical Model and Image Processing |
Keywords | DocType | Volume |
nonlinear interpolation technique,medical image | Journal | 53 |
Issue | ISSN | Citations |
4 | 1049-9652 | 3 |
PageRank | References | Authors |
0.94 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Long-Wen Chang | 1 | 532 | 51.82 |
| Hown-Wen Chen | 2 | 7 | 2.89 |
| Ju-Rone Ho | 3 | 3 | 0.94 |