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Improvement of image quality in diffuse optical tomography by use of full time-resolved data

机译:通过使用完整的时间分辨数据来改善漫射光学层析成像中的图像质量

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In the field of diffuse optical tomography (DOT), it is widely accepted that time-resolved (TR) measurement can provide the richest information on photon migration in a turbid medium, such as biological tissue. However, the currently available image reconstruction algorithms for TR DOT are based mostly on the cw component or some featured data types of original temporal profiles, which are related to the solution of a time-independent diffusion equation. Although this methodology can greatly simplify the reconstruction process, it suffers from low spatial resolution and poor quantitativeness owing to the limitation of effectively applicable data types. To improve image quality, it has been argued that exploiting the full TR data is essential. We propose implementation of a DOT algorithm by using full TR data and furthermore a variant algorithm with time slices of TR data to alleviate the computational complexity and enhance noise robustness. Compared with those algorithms where the featured data types are used, our evaluations on the spatial resolution and quantitativeness show that a significant improvement in imaging quality can be achieved when full TR data are used, which convinces the DOT community of the potential advantage of the TR domain over cw and frequency domains. (C) 2002 Optical Society of America. [References: 31]
机译:在漫射光学层析成像(DOT)领域,时间分辨(TR)测量可以提供有关混浊介质(例如生物组织)中光子迁移的最丰富信息,这一点已被广泛接受。但是,目前可用的TR DOT图像重建算法主要基于连续时间分量或原始时间剖面的某些特征数据类型,这与时间独立扩散方程的求解有关。尽管这种方法可以大大简化重建过程,但由于有效应用的数据类型的局限性,其空间分辨率低且定量性差。为了提高图像质量,已经有人提出充分利用TR数据是必不可少的。我们建议通过使用完整的TR数据来实现DOT算法,此外,还提出一种带有TR数据时间片的变体算法,以减轻计算复杂性并增强噪声鲁棒性。与使用特征数据类型的算法相比,我们对空间分辨率和定量性的评估表明,使用完整的TR数据可以显着提高成像质量,这使DOT社区相信TR的潜在优势连续频域和频域。 (C)2002年美国眼镜学会。 [参考:31]

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