Methods of Preprocessing Tomographic Images Taking into Account the Thermal Instability of the X-ray Tube


如何引用文章

全文:

开放存取 开放存取
受限制的访问 ##reader.subscriptionAccessGranted##
受限制的访问 订阅存取

详细

For correct numerical interpretation of tomographic images, i.e., estimates of the attenuation coefficients of objects, it is important to obtain reconstruction of high quality, which depends directly on the methods of processing experimental data. Data processing flow begins with its preparation for the application of the reconstruction algorithm. The necessary part of data processing contains the subtraction of the black field, normalization considering empty data, and taking logarithm. This part is not sufficient for obtaining high-quality reconstruction when working with real data since it is not ideal. Real data include noise and distortions due to changes in the setup geometrical parameters during the experiment. We have analyzed two possible types of data distortions during experiment and suggested corrections for them. The first one corrects thermal shifts regarding beam decentralization, and the second eliminates the effect of the polychromatic nature of X-ray radiation on the results of tomographic reconstruction. These methods were tested with both real and synthetic data. Both synthetic and real experiments show that suggested methods improve the reconstruction quality. In real experiments, the level of agreement between the automatic parameter adjustment and experts is about 90%.

作者简介

A. Ingacheva

Institute for Information Transmission Problems; Shubnikov Institute of Crystallography, Crystallography and Photonics Federal Scientific Research Center

编辑信件的主要联系方式.
Email: ingacheva@gmail.com
俄罗斯联邦, Bol’shoi Karetnyi per. 19, Moscow, 127051; Leninskii pr. 59, Moscow, 119333

A. Buzmakov

Shubnikov Institute of Crystallography, Crystallography and Photonics Federal Scientific Research Center

Email: ingacheva@gmail.com
俄罗斯联邦, Leninskii pr. 59, Moscow, 119333

补充文件

附件文件
动作
1. JATS XML

版权所有 © Allerton Press, Inc., 2019