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Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography

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Published on: January 30, 2016

Automatic synchrotron tomographic alignment schemes based on genetic algorithms and human-in-the-loop software.

Zhen Zhang¹, Xiaoxue Bi², Pengcheng Li²

¹National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, Anhui 230029, People's Republic of China.

Journal of Synchrotron Radiation

|January 5, 2023

Summary

This summary is machine-generated.

This study introduces an automated software method for aligning X-ray tomography systems, reducing experimental setup time and improving data acquisition efficiency for advanced imaging.

Keywords:

X-ray microscopy computed tomography genetic algorithms human-in-the-loop rotation-axis alignment sample alignment scanning tomography

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Last Updated: Aug 15, 2025

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Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages

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Published on: April 13, 2016

Area of Science:

Physics
Materials Science
Imaging Technology

Background:

Synchrotron-based tomography imaging is advancing, requiring high spatial and temporal resolutions.
Complex experimental setups with small probes and multi-dimensional scanning pose alignment challenges.
Current post-processing alignment methods are time-consuming and cannot fully correct errors.

Purpose of the Study:

To develop an automated alignment scheme for X-ray tomography systems.
To reduce human effort and beam time spent on experimental setup.
To improve the efficiency and accuracy of data acquisition.

Main Methods:

A software-based approach combining genetic algorithms and human intelligence was developed.
The method focuses on automatic alignment of the rotational axis and sample.
Alignment is performed both before and during data acquisition.

Main Results:

The automated scheme achieved excellent sub-pixel alignment efficiency.
The alignment process was completed in a short amount of time.
The approach demonstrated effectiveness for both rotational axis and sample alignment.

Conclusions:

The developed automated alignment scheme significantly enhances X-ray tomography experiments.
This method offers a time-efficient solution for complex alignment tasks.
The approach has strong potential for integration into future scanning tomography data acquisition systems.