Automated Tilt Series Alignment and Tomographic Reconstruction in IMOD

By David N. Mastronarde, Susannah R. Held. Journal of Structural Biology, 2016

704 citations recorded by the source corpus.

Automated tomographic reconstruction is now possible in the IMOD software package, including the merging of tomograms taken around two orthogonal axes. Several developments enable the production of high-quality tomograms. When using fiducial markers for alignment, the markers to be tracked through the series are chosen automatically; if there is an excess of markers available, a well-distributed subset is selected that is most likely to track well. Marker positions are refined by applying an edge-enhancing Sobel filter, which results in a 20% improvement in alignment error for plastic-embedded samples and 10% for frozen-hydrated samples. Robust fitting, in which outlying points are given less or no weight in computing the fitting error, is used to obtain an alignment solution, so that aberrant points from the automated tracking can have little effect on the alignment. When merging two dual-axis tomograms, the alignment between them is refined from correlations between local patches; a measure of structure was developed so that patches with insufficient structure to give accurate correlations can now be excluded automatically. We have also developed a script for running all steps in the reconstruction process with a flexible mechanism for setting parameters, and we have added a user interface for batch processing of tilt series to the Etomo program in IMOD. Batch processing is fully compatible with interactive processing and can increase efficiency even when the automation is not fully successful, because users can focus their effort on the steps that require manual intervention.

Subfields: Geophysics, Radiation, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/bf08b5d32f3bcf705ca5a6a90a0a95a97e272158

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Citations in the corpus

Construction, characterization, and immunization of nanoparticles that display a diverse array of influenza HA trimers (2020, methodology): “Images were aligned and reconstructed using IMOD [27, 28].”
AI-based structure prediction empowers integrative structural analysis of human nuclear pores (2022, methodology): “D. N. Mastronarde, S. R. Held, Automated tilt series alignment and tomographic reconstruction in IMOD.”