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首页> 外文会议>Conference on Photon Migration and Diffuse - Light Imaging; Jun 22-23, 2003; Munich, Germany >Three-Dimensional Diffuse Optical Tomography with a priori Anatomical Information
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Three-Dimensional Diffuse Optical Tomography with a priori Anatomical Information

机译：具有先验解剖学信息的三维漫射光学层析成像

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摘要

Diffuse Optical Tomography (DOT) image reconstruction is a challenging 3D problem with a relatively large number of unknowns. DOT poses a typical ill-posed problem usually plagued by under-determination, which complicates the inverse problem. Conventional image reconstruction algorithms can not provide high spatial resolution and may become computationally expensive and unreliable especially in the presence of noise. In this work, we extend our previous formulation for the 3D inverse DOT problem, where we focus to improve the spatial resolution and quantitative accuracy of 3D DOT images by using anatomical a priori information, which is specific to the medium of interest. Maximum A Posteriori (MAP) estimate of the image is formed based on the formulation of the image's probability density function, which is extracted from the available a priori anatomical information. An "alternating minimization" algorithm, which sequentially updates the unknown parameters, is used to solve the resulting optimization problem. Proposed method is evaluated in a 3D simulation experiment. Results demonstrate that the proposed method leads to significantly improved spatial resolution, quantitative accuracy and faster convergence than standard and regularized least squares solutions even in the presence of noise. As a result, the approach demonstrated in this paper both addresses the ill-posedness and balances the computation complexity vs. image quality trade-off in the 3D DOT inverse problem.
机译：漫射光学层析成像（DOT）图像重建是一个挑战性的3D问题，具有相对大量的未知数。 DOT提出了一个典型的不适定问题，通常会因测定不足而困扰，这会使反问题变得复杂。传统的图像重建算法不能提供高空间分辨率，并且可能变得计算量大且不可靠，尤其是在存在噪声的情况下。在这项工作中，我们扩展了3D逆DOT问题的先前公式，在此我们专注于通过使用特定于感兴趣介质的解剖先验信息来提高3D DOT图像的空间分辨率和定量准确性。基于图像的概率密度函数的公式来形成图像的最大后验（MAP）估计，该概率密度函数是从可用的先验解剖信息中提取的。依次更新未知参数的“替代最小化”算法用于解决最终的优化问题。在3D模拟实验中评估了提出的方法。结果表明，即使在存在噪声的情况下，与标准和正则化最小二乘解相比，所提出的方法也可以显着提高空间分辨率，定量精度和更快的收敛速度。结果，本文演示的方法既解决了不适情况，又在3D DOT逆问题中平衡了计算复杂度与图像质量之间的权衡。

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