Zhejiang Univ., Hangzhou.
IEEE Trans Med Imaging. 1992;11(1):70-5. doi: 10.1109/42.126912.
A solution algorithm for the image reconstruction problem with three criteria, maximum entropy, minimum nonuniformity and peakedness, and least square error between the original projection data and projection due to reconstruction is presented. Theoretical results of precedence properties which are respected by all noninferior solutions are first derived. These precedence properties are then incorporated into a multiple-criteria optimization framework to improve the computational efficiency. Comparisons of the new algorithm to the MART and MENT algorithms are carried out using computer-generated noise-free and Gaussian noisy projections. Results of the computational experiment and the efficiency of the multiobjective entropy optimization algorithm (MEOA) are reported.
提出了一种具有三个准则（最大熵、最小非均匀性和峰值度）和最小均方误差的图像重建问题的求解算法，用于重建数据与原始投影数据之间的投影。首先推导出所有非劣解都遵守的优先性理论结果。然后将这些优先性合并到多准则优化框架中，以提高计算效率。使用计算机生成的无噪声和高斯噪声投影，对新算法与 MART 和 MENT 算法进行了比较。报告了计算实验的结果和多目标熵优化算法（MEOA）的效率。
