首页> 外文会议>Conference on Photon Migration, Diffuse Spectroscopy, and Optical Coherence Tomography: Imaging and Functional Assessment, Jul 6-8, 2000, Amsterdam, the Netherlands >Measurement and model error assessment of a single pixel, frequency domain photon migration apparatus and diffusion model for imaging applications
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Measurement and model error assessment of a single pixel, frequency domain photon migration apparatus and diffusion model for imaging applications

机译:用于成像应用的单个像素的测量和模型误差评估,频域光子迁移装置和扩散模型

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摘要

Research into the near-infrared biomedical optical imaging has produced a multitude of inverse imaging algorithms. Recent experience has shown that when these algorithms are tested with experimental data, they falter due to a mismatch between observed and simulated measurements. When considering measurements for imaging, one must consider both measurement and model error. If data is recorded properly, then measurement error tends to be normally distributed with a mean of zero. Model error can be biased and spatially correlated due to a inaccuracies in the diffusion approximation, inaccurate parameter estimates, numerical error, and other factors. This contribution discusses trends in the measurement and model error observed from measurements on a single-pixel, frequency domain photon migration system developed for biomedical optical imaging. In order to reduce the model error bias, an empirical approach was applied to find experimental variables that significantly affect it. This approach reduced the mean of the model error on a test data set and produced a slight smoothing effect on its distribution. Image reconstruction attempts show that the modified data set produces an improved image over the image reconstructed from the raw data set. To our knowledge, this is the first time that model and measurement error information have been incorporated into a three dimensional image reconstruction algorithm.
机译:对近红外生物医学光学成像的研究产生了许多逆成像算法。最近的经验表明,当用实验数据对这些算法进行测试时,由于观察到的和模拟的测量值之间的不匹配,它们会动摇。考虑成像测量时,必须同时考虑测量误差和模型误差。如果正确记录了数据,则测量误差趋于以零为正态分布。由于扩散近似中的不准确,参数估计不准确,数值误差和其他因素,模型误差可能会发生偏差并在空间上相关。该文稿讨论了为生物医学光学成像开发的单像素频域光子迁移系统的测量结果以及从模型中观察到的模型误差的趋势。为了减少模型误差偏差,采用了一种经验方法来寻找对模型误差有重大影响的实验变量。这种方法减少了测试数据集上模型误差的平均值,并对其分布产生了轻微的平滑效果。图像重建尝试显示,与从原始数据集重建的图像相比,修改后的数据集产生了改进的图像。据我们所知,这是首次将模型和测量误差信息纳入三维图像重建算法中。

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