nDTomo

Introduction

This environment is designed for tomographic reconstruction using nDTomo, a Python-based software suite tailored for X-ray chemical imaging and computed tomography (CT). The platform is powered by the ASTRA Toolbox and PyTorch, supporting GPU-accelerated and CPU-based workflows.

Environment configuration

Installation directories

• nDTomo is installed both in /opt/nDTomo/ and within the conda environment ndtomo, including:
  • Core package modules
  • GUI launcher: nDTomo.gui.nDTomoGUI
  • Editable installation for development and customization
• ASTRA Toolbox is installed inside the Conda environment ndtomo.
• PyTorch is installed with CUDA 12.1 support in the same environment.
• Tutorial Notebooks are copied to /home/cloud/ndtomo_tutorials/
• Conda environment base: /opt/conda/

Usage examples

Launching the nDTomo GUI

When a terminal session is started, the ndtomo Conda environment should automatically be activated. If it becomes deactivated, it can be reactivated manually:

conda activate ndtomo

Within the activated ndtomo environment, launch the nDTomo GUI with:

python -m nDTomo.gui.nDTomoGUI

The GUI can also be started from the Ubuntu Applications menu by clicking the nDTomo GUI shortcut icon.

Additionally, there is a shortcut icon labeled nDTomo Tutorial (Jupyter) that opens a Jupyter Notebook with the ndtomo environment and preloaded tutorial notebook:

Working with Jupyter notebooks

Jupyter Notebook is also installed in the ndtomo Conda environment. It can be launched from the terminal with:

jupyter notebook

Tutorial notebooks from the nDTomo GitHub page are available in the /home/cloud/ndtomo_tutorials/ directory to help users get started:

Public job templates

The following job templates have been created for this environment and made public:

Version history

Version 0

Initial installation with:

• nDTomo (version 2025.5)
• ASTRA toolbox (version 2.3.1)
• PyTorch (version 2.5.1+cu121)

References

nDTomo

1. nDTomo github: https://github.com/antonyvam/nDTomo
2. nDTomo docs: https://ndtomo.readthedocs.io/
3. Citation: Vamvakeros, A., Papoutsellis, E., Dong, H., Docherty, R., Beale, A.M., Cooper, S.J., Jacques, S.D.M.J., nDTomo: A Python-Based Software Suite for X-ray Chemical Imaging and Tomography, 2025, https://github.com/antonyvam/nDTomo

ASTRA Toolbox

1. Astra Toolbox: https://www.astra-toolbox.com/
2. Astra Toolbox github: https://github.com/astra-toolbox/astra-toolbox
3. Citation 1: W. van Aarle, W. J. Palenstijn, J. Cant, E. Janssens, F. Bleichrodt, A. Dabravolski, J. De Beenhouwer, K. J. Batenburg, and J. Sijbers, “Fast and Flexible X-ray Tomography Using the ASTRA Toolbox”, Optics Express, 24(22), 25129-25147, (2016), http://dx.doi.org/10.1364/OE.24.025129
4. Citation 2: W. van Aarle, W. J. Palenstijn, J. De Beenhouwer, T. Altantzis, S. Bals, K. J. Batenburg, and J. Sijbers, “The ASTRA Toolbox: A platform for advanced algorithm development in electron tomography”, Ultramicroscopy, 157, 35–47, (2015), http://dx.doi.org/10.1016/j.ultramic.2015.05.002
5. Citation 3 (if using parallel beam GPU code): W. J. Palenstijn, K. J. Batenburg, and J. Sijbers, “Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)”, Journal of Structural Biology, vol. 176, issue 2, pp. 250-253, 2011, http://dx.doi.org/10.1016/j.jsb.2011.07.017

PyTorch

1. PyTorch: https://pytorch.org/