Tomosaic: efficient acquisition and reconstruction of teravoxel tomography data using limited-size synchrotron X-ray beams

被引:33
作者
Vescovi, Rafael [1 ,7 ]
Du, Ming [2 ]
de Andrade, Vincent [1 ]
Scullin, William [3 ]
Gursoy, Doga [1 ,4 ]
Jacobsen, Chris [1 ,5 ,6 ]
机构
[1] Argonne Natl Lab, Adv Photon Source, Argonne, IL 60439 USA
[2] Northwestern Univ, Dept Mat Sci, Evanston, IL 60208 USA
[3] Argonne Natl Lab, Argonne Leadership Comp Facil, Argonne, IL 60439 USA
[4] Northwestern Univ, Dept Elect Engn & Comp Sci, Evanston, IL 60208 USA
[5] Northwestern Univ, Dept Phys & Astron, Evanston, IL 60208 USA
[6] Northwestern Univ, Chem Life Proc Inst, Evanston, IL 60208 USA
[7] Univ Chicago, Dept Neurobiol, 947 East 58th St,MD 0928, Chicago, IL 60637 USA
来源
JOURNAL OF SYNCHROTRON RADIATION | 2018年 / 25卷
关键词
X-ray tomography; image alignment; image reconstruction; parallelized computing; IMAGE-RECONSTRUCTION; COMPUTED-TOMOGRAPHY; HIGH-RESOLUTION; MICROTOMOGRAPHY; !text type='PYTHON']PYTHON[!/text; REGISTRATION; BEAMLINE; ROTATION; MPI;
D O I
10.1107/S1600577518010093
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
X-rays offer high penetration with the potential for tomography of centimetre-sized specimens, but synchrotron beamlines often provide illumination that is only millimetres wide. Here an approach is demonstrated termed Tomosaic for tomographic imaging of large samples that extend beyond the illumination field of view of an X-ray imaging system. This includes software modules for image stitching and calibration, while making use of existing modules available in other packages for alignment and reconstruction. The approach is compatible with conventional beamline hardware, while providing a dose-efficient method of data acquisition. By using parallelization on a distributed computing system, it provides a solution for handling teravoxel-sized or larger datasets that cannot be processed on a single workstation in a reasonable time. Using experimental data, the package is shown to provide good quality three-dimensional reconstruction for centimetre-sized samples with sub-micrometre pixel size.
引用
收藏
页码:1478 / 1489
页数:12
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