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High-resolution restoration of diffuse optical images reconstructed by the photon average trajectories method

机译:通过光子平均轨迹法重建的漫反射光学图像的高分辨率恢复

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The possibility of improving the spatial resolution of diffuse optical images reconstructed by the photon average trajectories (PAT) method is substantiated. The PAT method recently presented by us is based on a concept of an average statistical trajectory for transfer of light energy, the photon average trajectory (PAT). The inverse problem of diffuse optical tomography (DOT) is reduced to solution of integral equation with integration along a conditional PAT. As a result the conventional algorithms of projection computed tomography can be used for fast reconstruction of diffuse optical images. In our recent works we have shown that the application of the backprojection algorithms with special filtration of shadows allows a 20% -gain in spatial resolution to be obtained. But the shortcoming of the backprojection algorithms is that they can not reconstruct accurately the object regions located close to the boundary. In the present paper we consider alternative approach to improve the spatial resolution, which may be applied to images reconstructed with the use of algebraic techniques. It is based on post-reconstruction restoration of images blurred due to averaging over spatial distributions of photons, which form the signal measured by the receiver. We suggest a spatially invariant blurring model to restore local regions of a diffuse image with the use of standard deconvolution algorithms. Two iterative non-linear algorithms: the maximum-likelihood algorithm and the Lucy-Richardson algorithm are considered. It is shown that both of them allow the spatial resolution to be improved. The effect of the improvement is identical to that obtained with the use of the backprojection algorithms.
机译:简化了通过光子平均轨迹(PAT)方法重建的扩散光学图像的空间分辨率的可能性。美国最近呈现的PAT方法基于用于传递光能的平均统计轨迹的概念,光子平均轨迹(PAT)。漫射光学断层扫描(点)的逆问题减小到整体方程的溶液,其沿着条件PAT的整合。结果,投影计算机断层扫描的传统算法可用于快速重建漫反射光学图像。在我们最近的作品中,我们表明,具有特殊过滤的背部注射算法的应用允许获得20%-Gain以获得待获得的空间分辨率。但反射算法的缺点是它们不能准确地重建位于靠近边界的物体区域。在本文中,我们考虑改善空间分辨率的替代方法,该方法可以应用于使用代数技术重建的图像。它基于由于在光子的空间分布上平均而模糊的图像的重建后恢复,其形成由接收器测量的信号。我们建议使用标准解卷积算法恢复弥漫图像的局部区域的空间不变模糊模型。考虑了两个迭代非线性算法:考虑了最大似然算法和Lucy-Richardson算法。结果表明,它们两个都允许改善空间分辨率。改进的效果与使用反扩展算法获得的效果相同。

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