基于多区域椭圆参数化描述的形状扩散光学层析成像方法研究  

A Pilot Investigation into Shape-Based DOT Methodology with Elliptic Parameterization of Multi-Domains

作　　者：阮平巧[1] 刘艳芳[1] 高峰[1] 赵会娟[1] 杨芳[1] 

机构地区：[1]天津大学精密仪器与光电子工程学院,天津300072

出　　处：《光学学报》2009年第9期2421-2427,共7页Acta Optica Sinica

基　　金：国家973计划(2006CB705700);国家自然科学基金(30870657;60678049);天津自然科学基金(07JCYBJC06600)资助课题

摘　　要：获取生物组织体的光学结构是扩散光学成像模式研究(如扩散光学层析技术和荧光分子成像技术)的核心内容。当假设组织器官中具有均匀光学参数时,光学结构的获取方法可归为基于形状的扩散光学层析成像(DOT)重建技术,该技术致力于同时重建组织器官的边界和内部光学参数。实现了二维的边界元正向模型,并与有限元正向模型的结果进行比较。反演问题中使用了截断奇异值(truncated-SVD)优化算法,并在40 dB噪声水平下用内部具有3个异质体的目标模型进行验证。数值结果表明,提出的图像重建算法具有良好的收敛性能,并能从噪声数据中准确恢复相应区域的形状参数和光学参数。Acquisition of the optical structures within a biological body is critical to all the diffuse light imaging modalities, such as diffuse optical tomography （DOT） and fluorescence molecular tomography （FMT）. On an assumption of the optical homogeneity within the organs, it can be cast as a shape-based DOT issue, which aims to simultaneously recover the smooth region boundaries and optical properties of the biological tissue. The boundary element method （BEM） is used for the forward modeling and implemented in two dimensions, and compared with those obtained from the finite element method （FEM） approach for the validation. A truncated singular value decomposition（truncated-SVD） optimization method is implemented for the inverse problem, which is evaluated in a domain with 3 heterogeneous inclusions at 40 dB noise level. The numerical simulations show that the methodology is very promising and of good convergence. The shape parameters and the optical coefficients can be reconstructed with good accuracy at a reasonable noise level.

关 键 词：生物光学 扩散光学层析成像 边界元法 椭圆参数化描述 截断奇异值分解法 逆问题 

分 类 号：Q63[生物学—生物物理学]