在计算机层析技术中投影数据的多目标优化
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摘要
在计算机层析技术 (CT)中 ,优化投影数据是改善重建图象质量的有效途径。为减弱噪声等因素对投影数据所造成的模糊 ,也为了寻求最佳唯一图象 ,为此以模糊数学和决策理论为基础 ,通过建立投影模糊指数函数及平方误差模糊指数函数 ,提出了一种称为多目标优化的新的模型 ,对投影数据进行优化。实验验证在微机上完成 ,首先在给定图象上作仿真采集并将所得投影数据加高斯噪声 ,然后用含噪声的及经多目标优化的两类投影数据分别完成图象重建 ,并把所得结果作对比分析。实验结果表明 ,所提出的多目标优化模型有较强的抗噪声能力 ,理论和实验有较好的一致性。
It is an effective way for improving quality of reconstructed images that projection data are optimized in the field of Computerized Tomography (CT). For lowering the fuzziness on projection data caused by lots of factors such as noise and getting the unigue optimal reconstructed image from noisy projection data further more, in this paper, the authors develop a new model named Multicriterion Optimization Model (MOP) for optimizing projection data. The model is structured based on the theories of fuzzy mathematics and decision making, via the method of deducing projection fuzzy exponent function and square error fuzzy exponent function. The experiments for validating the model have been carried out on personal computer (PC). At first, we make simulation collecting in the images presented and add Gauss Noise into the projection data obtained by simulation collecting, Then, complete the image reconstruction from noisy projection data by the solution without optimization and another solution with multicriterion optimization. Finally, compare and analysis the different results about images reconstructed by two different solutions. The experiment results indicate that the MOP in this paper has better consistency with the theory and practice as well as obvious advantage of antinoise ability.
It is an effective way for improving quality of reconstructed images that projection data are optimized in the field of Computerized Tomography (CT). For lowering the fuzziness on projection data caused by lots of factors such as noise and getting the unigue optimal reconstructed image from noisy projection data further more, in this paper, the authors develop a new model named Multicriterion Optimization Model (MOP) for optimizing projection data. The model is structured based on the theories of fuzzy mathematics and decision making, via the method of deducing projection fuzzy exponent function and square error fuzzy exponent function. The experiments for validating the model have been carried out on personal computer (PC). At first, we make simulation collecting in the images presented and add Gauss Noise into the projection data obtained by simulation collecting, Then, complete the image reconstruction from noisy projection data by the solution without optimization and another solution with multicriterion optimization. Finally, compare and analysis the different results about images reconstructed by two different solutions. The experiment results indicate that the MOP in this paper has better consistency with the theory and practice as well as obvious advantage of antinoise ability.
引文
[1] WANGYUNMEI ,LUWEIXUE .MulticriterionImageRe constructionandImplantation[J] .ComputerVisionGraph icsandImageProcessing ,1989,46( 2 ) :13 1 13 5 .
[2 ] WANGYUANMEI ,LUWEIXUE .MulticriterionMaxi mumEntropyImageReconstructionfromProjections[J] .IEEETransonMedicalImaging ,1992 ,( 11) :70 75 .
[3 ] 贺仲雄 .模糊数学及其应用 [M ] .天津 :天津科技出版社 ,1983 .
[4] 冯德益 .模糊数学方法及其应用 [M ] .北京 :地震出版社 ,1986.
[5 ] 刘政凯 ,翟建雄 .数字图象恢复与重建 [M ] .合肥 :中国科技大学出版社 ,1989.
[2 ] WANGYUANMEI ,LUWEIXUE .MulticriterionMaxi mumEntropyImageReconstructionfromProjections[J] .IEEETransonMedicalImaging ,1992 ,( 11) :70 75 .
[3 ] 贺仲雄 .模糊数学及其应用 [M ] .天津 :天津科技出版社 ,1983 .
[4] 冯德益 .模糊数学方法及其应用 [M ] .北京 :地震出版社 ,1986.
[5 ] 刘政凯 ,翟建雄 .数字图象恢复与重建 [M ] .合肥 :中国科技大学出版社 ,1989.
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