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3D shape based reconstruction of experimental data in Diffuse Optical Tomography

机译:基于3D形状的扩散光学层析成像中实验数据的重建

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摘要

Diffuse optical tomography (DOT) aims at recovering three-dimensional images of absorption and scattering parameters inside diffusive body based on small number of transmission measurements at the boundary of the body. This image reconstruction problem is known to be an ill-posed inverse problem, which requires use of prior information for successful reconstruction. We present a shape based method for DOT, where we assume a priori that the unknown body consist of disjoint subdomains with different optical properties. We utilize spherical harmonics expansion to parameterize the reconstruction problem with respect to the subdomain boundaries, and introduce a finite element (FEM) based algorithm that uses a novel 3D mesh subdivision technique to describe the mapping from spherical harmonics coefficients to the 3D absorption and scattering distributions inside a unstructured volumetric FEM mesh. We evaluate the shape based method by reconstructing experimental DOT data, from a cylindrical phantom with one inclusion with high absorption and one with high scattering. The reconstruction was monitored, and we found a 87% reduction in the Hausdorff measure between targets and reconstructed inclusions, 96% success in recovering the location of the centers of the inclusions and 87% success in average in the recovery for the volumes.
机译:漫射光学层析成像(DOT)的目的是根据在人体边界处的少量透射测量结果,恢复漫射体内的吸收和散射参数的三维图像。已知该图像重建问题是不适定的逆问题,其需要使用先验信息来成功重建。我们提出了一种基于形状的DOT方法,其中我们先验地假设未知物体由具有不同光学特性的不相交子域组成。我们利用球谐展开来参数化关于子域边界的重构问题,并引入基于有限元(FEM)的算法,该算法使用新颖的3D网格细分技术来描述从球谐系数到3D吸收和散射分布的映射在非结构化体积有限元网格中。我们通过从一个带有一个高吸收夹杂物和一个高散射夹杂物的圆柱体模型中重建实验DOT数据来评估基于形状的方法。监测了重建过程,我们发现目标和重建的夹杂物之间的Hausdorff测度降低了87%,恢复了夹杂物中心位置的成功率达到了96%,平均回收率达到了87%。

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