> For the complete documentation index, see [llms.txt](https://docs.imerit.net/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.imerit.net/how-to/export-data/download-dicom-segmentation-masks.md).

# Download DICOM Segmentation Masks

{% hint style="warning" %}
In previous versions, Hub automatically generated and provided links to ready-made segmentation .png masks for DICOMS in the export. This has now been deprecated.

The following workaround, however, will provide the exact same result.
{% endhint %}

{% hint style="info" %}
To obtain masks for annotations created with the Brush tool, simply activate the *Mask URLs* export field and click on the *brushDataUrl* URL in the export.
{% endhint %}

1. After having uploaded and annotated your DICOM files with a [Segmentation labeling tool](/labeling/labeling-tools/tools/segmentation.md), go to the *Export* tab.
2. In the Export tab, ensure the *Segmentation Points* toggle in the *Fields* dropdown is active.
3. Click on *Export* to get the export, and save the resulting .json file somewhere you'll remember.
4. Download [this .zip archive](https://github.com/angoai/convert-to-single-mask/archive/refs/heads/main.zip) containing our scripts to create masks from polygon or segmentation exports. Extract it, and move your .json file to this folder.
5. With a text editor, open the file `2_segmentation_to_single_mask.py` and replace the placeholder variable contents with your own data.
6. With a terminal, navigate to the folder and run `pip install -r requirements.txt` to install the required packages to run the Python script.
7. Within the terminal, run `python 2_segmentation_to_single_mask.py` to extract a .png mask from your export.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.imerit.net/how-to/export-data/download-dicom-segmentation-masks.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.