Title: Automatic projection image registration for nanoscale X-ray tomographic reconstruction

Abstract

Novel developments in X-ray sources, optics and detectors have significantly advanced the capability of X-ray microscopy at the nanoscale. Depending on the imaging modality and the photon energy, state-of-the-art X-ray microscopes are routinely operated at a spatial resolution of tens of nanometres for hard X-rays or ~10 nm for soft X-rays. The improvement in spatial resolution, however, has led to challenges in the tomographic reconstruction due to the fact that the imperfections of the mechanical system become clearly detectable in the projection images. Without proper registration of the projection images, a severe point spread function will be introduced into the tomographic reconstructions, causing the reduction of the three-dimensional (3D) spatial resolution as well as the enhancement of image artifacts. Here the development of a method that iteratively performs registration of the experimentally measured projection images to those that are numerically calculated by reprojecting the 3D matrix in the corresponding viewing angles is shown. Multiple algorithms are implemented to conduct the registration, which corrects the translational and/or the rotational errors. A sequence that offers a superior performance is presented and discussed. Going beyond the visual assessment of the reconstruction results, the morphological quantification of a battery electrode particle that has gonemore » through substantial cycling is investigated. The results show that the presented method has led to a better quality tomographic reconstruction, which, subsequently, promotes the fidelity in the quantification of the sample morphology« less

Authors:

Yu, Haiyan ^[1]; Xia, Sihao ^[2]; Wei, Chenxi ^[3]; Mao, Yuwei ^[4]; Larsson, Daniel ^[3]; Xiao, Xianghui ^[5]; Pianetta, Piero ^[3]; Yu, Young-Sang ^[6]; Liu, Yijin ^[3]

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+ Show Author Affiliations

1. Donghua Univ., Shanghai (China). College of Mechanical Engineering; SLAC National Accelerator Lab., Menlo Park, CA (United States). Stanford Synchrotron Radiation Lightsource (SSRL)
2. SLAC National Accelerator Lab., Menlo Park, CA (United States). Stanford Synchrotron Radiation Lightsource (SSRL); Nanjing Univ. of Science and Technology (China). School of Electronic and Optical Engineering
3. SLAC National Accelerator Lab., Menlo Park, CA (United States). Stanford Synchrotron Radiation Lightsource (SSRL)
4. Nanjing Univ. of Science and Technology (China). School of Computer Science and Technology
5. Argonne National Lab. (ANL), Argonne, IL (United States). Advanced Photon Source (APS)
6. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Advanced Light Source (ALS)

Publication Date:

Thu Nov 01 00:00:00 EDT 2018

Research Org.:

SLAC National Accelerator Lab., Menlo Park, CA (United States); Argonne National Lab. (ANL), Argonne, IL (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Sponsoring Org.:

USDOE Office of Science (SC), Basic Energy Sciences (BES); China Scholarship Council (CSC)

OSTI Identifier:

1476346

Alternate Identifier(s):

OSTI ID: 1559163

Grant/Contract Number:  

AC02-76SF00515; AC02-05CH11231

Resource Type:

Accepted Manuscript

Journal Name:

Journal of Synchrotron Radiation (Online)

Additional Journal Information:

Journal Name: Journal of Synchrotron Radiation (Online); Journal Volume: 25; Journal Issue: 6; Journal ID: ISSN 1600-5775

Publisher:

International Union of Crystallography

Country of Publication:

United States

Language:

English

Subject:

47 OTHER INSTRUMENTATION; 42 ENGINEERING; transmission X-ray microscopy; nanoscale tomography; image registration; tomographic reconstruction