---
title: "nDTomo"
url: "https://help.dectris.cloud/en/article/ndtomo"
language: "en"
last_updated: "2026-07-16T01:08:37.496Z"
---

# nDTomo

## **Introduction**

[This environment](https://app.dectris.cloud/sections/library/environments/public?id=019707fb-c675-7b50-8787-cfc90e958a00) is designed for tomographic reconstruction using [**nDTomo**](https://ndtomo.readthedocs.io/en/master/), a Python-based software suite tailored for X-ray chemical imaging and computed tomography (CT). The platform is powered by the [**ASTRA Toolbox**](https://astra-toolbox.com/) and [**PyTorch**](https://pytorch.org/), 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:

```plaintext
conda activate ndtomo
```

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

```plaintext
python -m nDTomo.gui.nDTomoGUI
```

![](https://cdn-assets.productfruits.com/89c778f5-b6a6-469d-8143-e3ef2105f8e5)

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:

![](https://cdn-assets.productfruits.com/78c6a2d2-c747-4824-8120-75f358b7dcd0)

### **Working with Jupyter notebooks**

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

```plaintext
jupyter notebook
```

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

![](https://cdn-assets.productfruits.com/1daf58b0-4db5-427d-b602-88272409312d)

## **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](https://github.com/antonyvam/nDTomo)
2.  nDTomo docs: [https://ndtomo.readthedocs.io/](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](https://github.com/antonyvam/nDTomo)

### **ASTRA Toolbox**

1.  Astra Toolbox: [https://www.astra-toolbox.com/](https://www.astra-toolbox.com/)
2.  Astra Toolbox github: [https://github.com/astra-toolbox/astra-toolbox](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](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](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](http://dx.doi.org/10.1016/j.jsb.2011.07.017)

### **PyTorch**

1.  PyTorch: [https://pytorch.org/](https://pytorch.org/)