Tomography processing notes

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This article/section is a stub — probably a pile of half-sorted notes, is not well-checked so may have incorrect bits. (Feel free to ignore, fix, or tell me)

See also EM software notes

On gold fiducials

Apparently in theory there's

  • Au11 (0.8mn) a.k.a. undecagold
  • Au25 (0.9mn)
  • Au38 (1.1nm)
  • Au68 (1.3nm)
  • 1.4nm, often referred to as nanogold
  • Au102 (1.5nm)
  • 1.8nm (a.k.a. Ni-NTA–Nanogold(verify))
  • Au114 (2.0nm)
  • Much larger is colloidal gold (so these sizes are a little more approximate), often one of
    • 5nm
    • 10nm
    • 15nm
    • 20nm
    • 25nm

Apparently most commonly it's 5nm or 10nm, sometimes nanogold(verify).

See also "[Site-specific biomolecule labeling with gold clusters." (PMC3568671)

In general

The overall steps in reconstruction

A typical approach is described e.g. in imod. See e.g.

the overall diagram in "Automated tilt series alignment and tomographic reconstruction in IMOD"
See also "Tomography Guide for IMOD Version 4.9"
and a list of parts (some optional) in the batchruntomo man page.
and its tutorial

Required input

  • a series of images - a tilt series
  • roughly known angles for each such image
in IMOD: MRC header, text file, or given interval
  • tilt axis angle (=basically the rotation between sensor/image and tilt axis, so the direction it rotates on within the image. It would be nice if this were mechanically aligned to the sensor('s longest dimension), but rarely true for practical reasons)
if wrong, the coarse alignment will fail
±5 degrees is fine because it's usually a parameter it's finding in fine alignment
...but coarse alignment will probably fail if it's more than ~5 degrees off (because it's trying to accounting for the direction things squeeze in(verify))
IMOD: MRC header, or given value

Useful input:

  • knowing fiducial bead size eases finding them
  • Target bead amount helps using what you have.
  • Sample thickness
can be calculated from bead set (but not under all conditions, so a sensible fallback value can helps)
used to not make the back-projected volume much larger than the sample (roughly "you can stop this far away from the beads")
also relevant to rotating the sample within that volume to align with one axis, for more sensible slicing, and smaller volume

Steps, roughly

optional: remove dark/blank images

remove X-rays, pixel defects

useful for normalization step
IMOD: ccderaser

Rough alignment

basically, minimize it jumping about
otherwise not solving anything, but it assists fine alinment
(e.g. somewhat specialized cross-correlation)
IMOD: tiltxcorr

Finer alignment, by one of:

  • alignment using fiducial model (fiducials are small high-contrast things, typically gold beads)
  • fiducialless alignment, e.g. patch tracking / feature tracking
  • skipping (effectively assumes rough alignment is enough, which it basically never is)

model/correct CTF (optional)

only really required for higher resolution, which you may not need

remove fiducial markers from images

would be disturbing influence in tomogram


make tomogram from the stack

  • e.g. (Weighted) BackProjection (WBP), or SIRT (Simultaneous Iterative Reconstruction Technique)

slice out just the specimen (optional, but rather practical)

Optional: noise reduction via NAD (nonlinear anisotropic diffusion) filter

Where applicable: combine dual axis tomogram

Where useful: Subvolume averaging

if you have multiple of the same thing within a tomogram that you want to combine (sort of single particle style)


  • Fiducial tracking can be done by manually telling it which correspond, or doing it via IMOD, or RAPTOR, or other.
Doing fine-detail alignment with fiducials is a nontrivial optimization problem.
Using more makes for finer detail in the alignment (averages and noise),
but also requires and kicking out the ones that seem to disagree with the consensus,
because a few bad cases would throw off otherwise detailed averages.
IMOD: imodfindbeads, autofidseed, others
  • IMOD goes to 3D twice, first for something to work on, later for a cleaned version. There seem to be a few reasons for this.


Etomo runs you through the steps with some interaction in each.

batchruntomo is essentially a job manager

you give it directive files (adocs)
...with pre-set steps; you can run parts at a time (see -start, -end), useful for inspection before you continue, and to redo things with different parameters.

The list of directives:

Directives are sorted into:

  • setupset - mostly describes collection and dataset
  • com-param - parameters for programs (like in .com files)
  • run-time - parameters interpreted by batchruntomo or etomo (verify)


PEET (Particle Estimation for Electron Tomography) [1]

RAPTOR (Robust Alignment and Projection Estimation for Tomographic Reconstruction) used to be separate, and is now integrated, and a more automatic alternative. [2]