Dehghani Hamid, Srinivasan Subhadra, Pogue Brian W, Gibson Adam
School of Computer Science, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.
Philos Trans A Math Phys Eng Sci. 2009 Aug 13;367(1900):3073-93. doi: 10.1098/rsta.2009.0090.
The development of diffuse optical tomography as a functional imaging modality has relied largely on the use of model-based image reconstruction. The recovery of optical parameters from boundary measurements of light propagation within tissue is inherently a difficult one, because the problem is nonlinear, ill-posed and ill-conditioned. Additionally, although the measured near-infrared signals of light transmission through tissue provide high imaging contrast, the reconstructed images suffer from poor spatial resolution due to the diffuse propagation of light in biological tissue. The application of model-based image reconstruction is reviewed in this paper, together with a numerical modelling approach to light propagation in tissue as well as generalized image reconstruction using boundary data. A comprehensive review and details of the basis for using spatial and structural prior information are also discussed, whereby the use of spectral and dual-modality systems can improve contrast and spatial resolution.
扩散光学层析成像作为一种功能成像模态的发展在很大程度上依赖于基于模型的图像重建方法。从组织内光传播的边界测量中恢复光学参数本质上是一项艰巨的任务,因为该问题是非线性、不适定和病态的。此外,尽管通过组织的光传输所测量的近红外信号提供了高成像对比度,但由于光在生物组织中的漫射传播,重建图像的空间分辨率较差。本文综述了基于模型的图像重建的应用,以及组织中光传播的数值建模方法和使用边界数据的广义图像重建。还讨论了使用空间和结构先验信息的基础的全面综述和细节,由此光谱和双模态系统的使用可以提高对比度和空间分辨率。