title: Alignment of cryo-electron tomography datasets.
abstract: Data acquisition of cryo-electron tomography (CET) samples described in previous chapters involves relatively imprecise mechanical motions: the tilt series has shifts, rotations, and several other distortions between projections. Alignment is the procedure of correcting for these effects in each image and requires the estimation of a projection model that describes how points from the sample in three-dimensions are projected to generate two-dimensional images. This estimation is enabled by finding corresponding common features between images. This chapter reviews several software packages that perform alignment and reconstruction tasks completely automatically (or with minimal user intervention) in two main scenarios: using gold fiducial markers as high contrast features or using relevant biological structures present in the image (marker-free). In particular, we emphasize the key decision points in the process that users should focus on in order to obtain high-resolution reconstructions.
authors.affiliation: Department of Electrical Engineering, Stanford University, Stanford, California, USA.
authors.forename: Fernando
authors.initials: F
authors.lastname: Amat
authors.forename: Daniel
authors.initials: D
authors.lastname: Castaño-Diez
authors.forename: Albert
authors.initials: A
authors.lastname: Lawrence
authors.forename: Farshid
authors.initials: F
authors.lastname: Moussavi
authors.forename: Hanspeter
authors.initials: H
authors.lastname: Winkler
authors.forename: Mark
authors.initials: M
authors.lastname: Horowitz
mesh_terms: D020285:Cryoelectron Microscopy / Q000379:methods*; D055032:Electron Microscope Tomography / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*