用遗传算法反演类上皮组织模型的偏振散射光谱

基于生物组织的粒状模型以及光谱对米氏(Mie)散射体形态的灵敏性,构建了类上皮组织模型的偏振后向散射光谱反演模型。针对反演模型的多参量、多极值、非线性,涉及到非常复杂的三角函数计算,模型空间极小的特点,采用每代保留最优个体的浮点遗传算法对类上皮组织模型的偏振后向散射光谱反演。对编码策略、适值调整策略及选择策略进行了讨论。研究结果表明:经过70代反演迭代,每个参量的相对误差趋于稳定,最小的达到0.02%左右,最大的不超过3%。采用基于实数编码的遗传算法能从偏振散射光谱中同时反演获得表层粒子的形态参量,具有全局收敛性和良好的反演精度与抗噪声能力。

Inversion of Polarized Light Scattering Spectra of Epitheliumlike Tissue Phantom by Genetic Algorithm

Polarized light backscattering spectra invertion model is established for epitheliumlike tissue phantom based on particles model of biological tissue and sensitivity of spectra to Mie scatters morphology.This inversion model is of multiple parameters,multiple extreme values and nonlinear,complicated trigonometric calculation is involved,and the model space is limited.Thus,floating genetic algorithms(FGAs),which reserves the optimal unit for every epoch,are applied to invert polarized light backscattering spectra for epitheliumlike tissue phantom.The strategies for encode,fitness adjusting and selection are discussed.The results indicate that,with 70 iteration epochs the relative error for every parameter inclines to be stable,about 0.02% for the minimal and less than 3% for the maximal.The genetic algorithm based on real encode can obtain the morphological parameters of the upper layer simultaneously by inverting the polarized light backscattering spectra,with global convergence,high inversion precision and robustness.