基于主成分分析的荧光分子断层成像

Fluorescence molecular tomography based on principal component analysis

随着全角度非接触式成像系统的开发与应用,较大规模的多投影荧光数据能够降低荧光分子断层成像(FMT)重建问题病态性,提高重建图像质量,已广泛应用于逆问题。但采用如此大规模的数据进行重建需要消耗大量的计算内存和花费较长的计算时间。为了解决该问题,采用主成分分析对原始FMT投影数据降维,在此基础上结合稀疏正则化算法进行重建。设计了圆柱仿真实验和数字鼠仿真实验。实验结果表明,在不影响重建结果的前提下,经过主成分分析降维后投影数据规模减小,FMT的重建时间缩短大约10倍。

With the development of non-contact imaging system ,multi fluorescence projections data can be obtained to reduce the ill-posedness of FMT and improve the quality of reconstruction images ,which has been widely used in the inverse problem .How-ever ,such a large scale of data of reconstruction needs a large amount of computational memory and time .An accelerated recon-struction method for FM T based on principal components analysis （PCA ） is presented to reduce the dimension of the inverse problem ;and then the sparse regularization algorithm is used for reconstruction .Simulation experiments are performed to verify the feasibility of the proposed method .The results demonstrate that the proposed method can accelerate reconstruction of FMT almost without quality degradation .