| 采用两层级联神经网络从少量投影重构二维图像 |
| |
| 引用本文： | 王静,孙宏伟,张树生,王飞.采用两层级联神经网络从少量投影重构二维图像[J].计算机辅助设计与图形学学报,2004,16(9):1284-1288. |
| |
| 作者姓名： | 王静 孙宏伟 张树生 王飞 |
| |
| 作者单位： | 西北工业大学现代设计与集成制造教育部重点实验室,西安,710072 |
| |
| 基金项目： | 航天创新基金 (天科研 2 0 0 1[181] )资助 |
| |
| 摘 要： | 文中算法第一级建立像素到其吸收系数的映射；第二级建立图像吸收系数矩阵到射线投影值的映射；最后由一级网络的输出构建吸收系数矩阵．该算法可以在较少投影数据量的条件下提高重建图像质量，为火箭发动机等大体积产品的无损检测或反求提供支撑技术．
|
| 关 键 词： | 图像二维重构 投影 CT 两层级联 神经网络 吸收系数 |
Two-Dimensional Image Reconstruction from Small Amount of Projection Paths by Using Joint Two-Grade Neural Network |
| |
| Wang Jing,Sun Hongwei,Zhang ShuSheng,Wang Fei.Two-Dimensional Image Reconstruction from Small Amount of Projection Paths by Using Joint Two-Grade Neural Network[J].Journal of Computer-Aided Design & Computer Graphics,2004,16(9):1284-1288. |
| |
| Authors: | Wang Jing Sun Hongwei Zhang ShuSheng Wang Fei |
| |
| Abstract: | The first grade neural network maps the pixels to their attenuation coefficient, then the second grade maps the attenuation coefficient matrix to projection data. Finally the image is reconstructed from attenuation coefficient matrix through the trained neural network in the first grade. Such an approach can support the nondestructive test or reverse engineering for rocket engine or other huge volume products. |
| |
| Keywords: | two-dimensional image reconstruction small amount of projection computerized tomography joint two-grade neural network attenuation coefficient |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
