Bimodal imaging at ICON using neutrons and X-rays

被引:29
|
作者
Kaestner, A. P. [1 ]
Hovind, J. [1 ]
Boillat, P. [1 ]
Muehlebach, C. [1 ]
Carminati, C. [1 ]
Zarebanadkouki, M. [2 ]
Lehmann, E. H. [1 ]
机构
[1] Paul Scherrer Inst, Lab Neutron Scattering & Imaging, Neutron Imaging & Activat Grp, CH-5232 Villigen, Switzerland
[2] Georg August Univ Goettingen, Div Soil Hydrol, D-37077 Gottingen, Germany
关键词
Neutron imaging; X-ray imaging; computed tomography; bimodal imaging; beamline; calibration;
D O I
10.1016/j.phpro.2017.06.043
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
For experiments with low contrast between the relevant features it can be beneficial to add a second modality to reduce ambiguity. At Paul Scherrer Institut the two neutron imaging facilities NEUTRA (thermal neutrons) and ICON (cold neutrons) we have installed X-ray beamlines for on-site bimodal imaging with neutrons and X-rays. This allows us to leave the sample untouched in the sample environment throughout an experiment and to reduce the waiting times between acquisitions using each modality. The applications and energy ranges of the X-ray installations are different at the two facilities. At NEUTRA larger samples are intended (60-320kV) and at ICON small samples and simultaneous acquisition are intended (40-150kV). Here, we report the more recent installation at ICON. The X-ray beamline uses a cone beam source and is arranged across the neutron beamline. The beamline is designed to allow up to ten times magnification. This matches the voxel-size that can be achieved with the micro-setup for neutrons. The oblique arrangement of the X-ray beamline further makes real-time acquisition possible since both modalities have a free view of the sample at any time. Reconstruction of cone beam data requires more knowledge about the beam geometry and sample position. Therefore, the beamline is equipped with laser based distance sensors and a calibration procedure has been developed to increase the accuracy of the reconstruction. The purpose of using multimodal acquisition is to fuse the data in a way that enhances the output of the experiment. We demonstrate the current system performance and provide a basic analysis with experiment data. (C) 2017 The Authors. Published by Elsevier B.V.
引用
收藏
页码:314 / 321
页数:8
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