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实现和评估定量中子成像中的黑体偏置校正。

Implementation and assessment of the black body bias correction in quantitative neutron imaging.

机构信息

Laboratory for Neutron Scattering and Imaging, Paul Scherrer Institut, Villigen, Switzerland.

Electrochemistry Laboratory, Paul Scherrer Institut, Villigen, Switzerland.

出版信息

PLoS One. 2019 Jan 4;14(1):e0210300. doi: 10.1371/journal.pone.0210300. eCollection 2019.

DOI:10.1371/journal.pone.0210300
PMID:30608985
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6319815/
Abstract

We describe in this paper the experimental procedure, the data treatment and the quantification of the black body correction: an experimental approach to compensate for scattering and systematic biases in quantitative neutron imaging based on experimental data. The correction algorithm is based on two steps; estimation of the scattering component and correction using an enhanced normalization formula. The method incorporates correction terms into the image normalization procedure, which usually only includes open beam and dark current images (open beam correction). Our aim is to show its efficiency and reproducibility: we detail the data treatment procedures and quantitatively investigate the effect of the correction. Its implementation is included within the open source CT reconstruction software MuhRec. The performance of the proposed algorithm is demonstrated using simulated and experimental CT datasets acquired at the ICON and NEUTRA beamlines at the Paul Scherrer Institut.

摘要

我们在本文中描述了实验过程、数据处理和黑体校正的量化：一种基于实验数据补偿定量中子成像中散射和系统偏差的实验方法。该校正算法基于两个步骤；散射分量的估计和使用增强的归一化公式进行校正。该方法将校正项纳入图像归一化过程中，该过程通常仅包括开束和暗电流图像（开束校正）。我们的目的是展示其效率和可重复性：我们详细说明了数据处理程序，并定量研究了校正的效果。它的实现包含在开源 CT 重建软件 MuhRec 中。所提出的算法的性能使用在保罗谢勒研究所的 ICON 和 NEUTRA 光束线上获得的模拟和实验 CT 数据集进行了演示。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/bb07d73d1064/pone.0210300.g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/97a5c6fe731a/pone.0210300.g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/8d3ffd097980/pone.0210300.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/44465787b3aa/pone.0210300.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/b1d355484b04/pone.0210300.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/e6bbe0e3acd5/pone.0210300.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/c1903673e783/pone.0210300.g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/208cba9055fd/pone.0210300.g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/28bdb571b4ff/pone.0210300.g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/bb07d73d1064/pone.0210300.g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/97a5c6fe731a/pone.0210300.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/80b50d7e0d3a/pone.0210300.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/b0e9efe8e653/pone.0210300.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/d9cceb2df68a/pone.0210300.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/c4ef15084c32/pone.0210300.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/7d1f2605e334/pone.0210300.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/8d3ffd097980/pone.0210300.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/44465787b3aa/pone.0210300.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/b1d355484b04/pone.0210300.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/e6bbe0e3acd5/pone.0210300.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/c1903673e783/pone.0210300.g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/208cba9055fd/pone.0210300.g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/28bdb571b4ff/pone.0210300.g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fd2/6319815/bb07d73d1064/pone.0210300.g014.jpg

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