A methodology for finding the optimal iteration number of the SIRT algorithm for quantitative Electron Tomography

WRAP: A wavelet-regularised reconstruction algorithm for magnetic vector electron tomography

Magnetic vector electron tomography (VET) is a promising technique that enables better understanding of micro- and nano-magnetic phenomena through the reconstruction of 3D magnetic fields at high spatial resolution. Here we introduce WRAP (Wavelet Regularised A Program), a reconstruction algorithm for magnetic VET that directly reconstructs the magnetic vector potential A using a compressed sensing framework which regularises for sparsity in the wavelet domain. We demonstrate that using WRAP leads to a significant increase in the fidelity of the 3D reconstruction and is especially robust when dealing with very limited data; using datasets simulated with realistic noise, we compare WRAP to a conventional reconstruction algorithm and find an improvement of ca. 60% when averaged over several performance metrics. Moreover, we further validate WRAP's performance on experimental electron holography data, revealing the detailed magnetism of vortex states in a CuCo nanowire. We believe WRAP represents a major step forward in the development of magnetic VET as a tool for probing magnetism at the nanoscale.

Electron tomography-a tool for ultrastructural 3D visualization in cell biology and histology

Electron tomography (ET) was developed to overcome some of the problems associated reconstructing three-dimensional (3D) images from 2D election microscopy data from ultrathin slices. Virtual sections of semithin sample are obtained by incremental rotation of the target and this information is used to assemble a 3D image. Herein, we provide an instruction to ET including the physical principle, possibilities, and limitations. We review the development of innovative methods and highlight important investigations performed in our department and with our collaborators. ET has opened up the third dimension at the ultrastructural level and represents a milestone in structural molecular biology.