Time-of-flight (ToF) neutron imaging offers complementary attenuation contrast to x-ray computed tomography, coupled with the ability to extract additional information from the variation in attenuation as a function of neutron energy (ToF) at every point (voxel) in the image. In particular, Bragg edge positions provide crystallographic information and therefore enable the identification of crystalline phases directly. Here we demonstrate Bragg edge tomography with high spatial and spectral resolution. We propose a new iterative tomographic reconstruction method with a tailored regularisation term to achieve high quality reconstruction from low-count data, where conventional filtered back-projection (FBP) fails. The regularisation acts in a separated mode for spatial and spectral dimensions and favours characteristic piece-wise constant and piece-wise smooth behaviour in the respective dimensions. The proposed method is compared against FBP and a state-of-the-art regulariser for multi-channel tomography on a multi-material phantom. The proposed new regulariser which accommodates specific image properties outperforms both conventional and state-of-the-art methods and therefore facilitates Bragg edge fitting at the voxel level. The proposed method requires significantly shorter exposures to retrieve features of interest. This in turn facilitates more efficient usage of expensive neutron beamline time and enables the full utilisation of state-of-the-art high resolution detectors.
Bibliographical noteFunding Information:
This work was funded by EPSRC grants A Reconstruction Toolkit for Multichannel CT (EP/P02226X/1), CCPi: Collaborative Computational Project in Tomographic Imaging (EP/M022498/1 and EP/T026677/1). We gratefully acknowledge beamtime RB1820541 at the IMAT Beamline of the ISIS Neutron and Muon Source, Harwell, UK. E A was partially funded by the Federal Ministry of Education and Research (BMBF) and the Baden-W rttemberg Ministry of Science as part of the Excellence Strategy of the German Federal and State Governments. J S J was partially supported by The Villum Foundation (Grant No. 25893). W R B L acknowledges support from a Royal Society Wolfson Research Merit Award. P J W and R W acknowledge support from the European Research Council Grant No. 695638 CORREL-CT.
© 2021 The Author(s). Published by IOP Publishing Ltd.