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Preprocessing

Introduction

This is a quick guide on how to use the tomo_preprocessing module for MemBrain-seg.

In order to improve the segmentation performance of MemBrain-seg on your tomograms, it may be beneficial to first perform some preprocessing to "normalize" the tomograms to similar styles as the training data.

This module currently allows you to use the following preprocessing methods:

  • Pixel size matching: Rescaling of your tomogram to a similar pixel size as the training data
  • Fourier amplitude matching: Rescaling of Fourier components to pronounce different features in the tomograms (adapted from DeePiCt)
  • Deconvolution: Deconvolution filter to enhance tomogram contrast (described in the Warp publication.)

Table of Contents

When to use what?

We are still exploring when it makes sense to use which preprocessing technique. But here are already some rules of thumb:

  1. Whenever your pixel sizes differs by a lot from around 10-12Å / pixel, you should consider using pixel size matching. We recommend to match to a pixel size of 10Å.
    It is also possible to do this rescaling on-the-fly, see our segmentation instructions.
  2. The Fourier amplitude matching only works in some cases, depending on the CTFs of input and target tomograms. Our current recommendation is: If you're not satisfied with MemBrain's segmentation performance, why not give the amplitude matching a shot?
  3. Deconvolution: This can make sense if your input tomogram has a very low signal-to-noise ratio. We still recommend Cryo-CARE as a denoising method, but this deconvolution can provide an easy-to-use alternative.

Usage

You can control all commands of this preprocessing module by typing tomo_preprocessing+ some options.
To view all available commands, use:

tomo_preprocessing --help

For help on a specific command, use:

tomo_preprocessing <command> --help

Available Commands

  • match_pixel_size: Tomogram rescaling to specified pixel size. Example:
    tomo_preprocessing match_pixel_size --input-tomogram <path-to-tomo> --output-path <path-to-output> --pixel-size-out 10.0 --pixel-size-in <your-px-size>`
  • match_seg_to_tomo: Segmentation rescaling to fit to target tomogram's shape. Example:
    tomo_preprocessing match_seg_to_tomo --seg-path <path-to-seg> --orig-tomo-path <path-to-tomo> --output-path <path-to-output>`
  • extract_spectrum: Extracts the radially averaged amplitude spectrum from the input tomogram. Example:
    tomo_preprocessing extract_spectrum --input-path <path-to-tomo> --output-path <path-to-output>
  • match_spectrum: Match amplitude of Fourier spectrum from input tomogram to target spectrum. Example:
    tomo_preprocessing match_spectrum --input <path-to-tomo> --target <path-to-spectrum> --output <path-to-output>
  • deconvolve: Perform the deconvolution filter to enhance tomogram contrast. Example: 
    tomo_preprocessing deconvolve --input <path-to-tomo> --output <path-to-output> --pixel-size <your-pixel-size>

Pixel Size Matching

Pixel size matching is recommended when your tomogram pixel sizes differs strongly from the training pixel size range (roughly 10-14Å).
IMPORTANT NOTE: MemBrain-seg can now also perform the rescaling on-the-fly during segmentation, making the below worklow redundant if you are not interested in the rescaled tomograms. You can check the on-the-fly rescaling at our segmentation instructions

If you prefer to not do it on-the-fly, you can perform the pixel size matching using the command

tomo_preprocessing match_pixel_size --input-tomogram <path-to-tomo> --output-path <path-to-output> --pixel-size-out 10.0 --pixel-size-in <your-px-size>

after adjusting the paths to your respective tomograms. Afterwards, you can perform MemBrain's segmentation on the rescaled tomogram (i.e. the one specified in --output-path).
Now, this new segmentation does not have the same shape as the original non-pixel-size-matched tomogram. To rescale the new segmentation to the original tomogram again, you can use

tomo_preprocessing match_seg_to_tomo --seg_path <path-to-seg> --orig-tomo-path <path-to-tomo> --output-path <path-to-output>

where the --seg-pathis the segmentation created by MemBrain and the --orig-tomo-pathis the original tomogram before rescaling to the new pixel size.
The output of this function will be MemBrain's segmentation, but matched to the pixel size of the original tomogram.

Fourier Amplitude Matching

Fourier amplitude matching is performed in two steps:

  1. Extraction of the target Fourier spectrum:
    tomo_preprocessing extract_spectrum --input-path <path-to-tomo> --output-path <path-to-output>
    This extracts the radially averaged Fourier spectrum and stores it into a .tsv file.
  2. Matching of the input tomogram to the extracted spectrum:
    tomo_preprocessing match_spectrum --input <path-to-tomo> --target <path-to-spectrum> --output <path-to-output>
    Now, the input tomograms Fourier components are re-scaled based on the equalization kernel computed from the input tomogram's radially averaged Fourier intensities, and the previously extracted .tsv file.

Deconvolution

Deconvolution can be applied in a single step as preprocesing before performing the segmentation using the command 

tomo_preprocessing deconvolve --input <path-to-tomo> --output <path-to-output> --pixel-size <your-pixel-size>