> 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/data/importing-assets/bundled-assets/importing-multiple-single-frame-dicom-files-as-a-3d-dicom-series.md).

# Importing Multiple Single-Frame DICOM Files as a 3D NRRD Asset

You may group together single-frame 2D DICOM files and upload them to Hub as a single 3D NRRD asset.

Assets uploaded this way are opened in the [Medical Labeling Editor](/labeling/labeling-editor-interface/medical-labeling-editor.md), rather than the DICOM labeling editor.

{% hint style="warning" %}
This functionality is only available for single-frame 2D DICOM files.
{% endhint %}

You may upload such multi-DICOM assets using the *Cloud Import* and the *File Explorer* methods outlined below. During upload, Ango Hub converts the grouped DICOM files into one NRRD file.

## Importing DICOM Files as NRRD Assets using the Cloud Upload Method

Prepare a JSON like the following, where each URL points to a DICOM you'd like to include in the asset. The order of the URLs will determine the order in which images will be presented to the annotator in the series.

The following JSON will import two NRRD assets:

```json
[
  {
    "externalId": "my-asset-external-id-1",
    "dataset": [
      "https://url.com/65c18c8b-4513-4a0a-b876-1aeb2e0908ec.dcm",
      "https://url.com/b0b70590-e4cc-42ef-8537-3ee3f7917fed.dcm",
      "https://url.com/38e11364-1ce0-417a-9e38-436468c555ce.dcm",
      "https://url.com/eff59355-03bd-447f-aa47-46028f90c2e6.dcm"
    ]
  },
  {
    "externalId": "my-asset-external-id-2",
    "dataset": [
      "https://url.com/65c18c8b-4513-4a0a-b876-123456789012.dcm",
      "https://url.com/b0b70590-e4cc-42ef-8537-234456566787.dcm",
      "https://url.com/38e11364-1ce0-417a-9e38-876345383488.dcm",
      "https://url.com/eff59355-03bd-447f-aa47-319485019239.dcm"
    ]
  }
]
```

From your project dashboard, go to the *Assets* tab and click on *Add Data*. Then, enter the *Cloud Storage* section and drag and drop your JSON on the file upload field.

Enable the "*Upload individual DICOM frames as single NRRD file*" checkbox on the left.

Then, press on *Upload*. Your DICOM files will be uploaded and converted into one NRRD asset.

If your DICOM files are in a private bucket, ensure you select the appropriate [storage integration](/data/storages.md) from the list on the left.

If Ango Hub cannot convert the DICOM files into an NRRD asset, the asset will remain in the *Assets* tab with a *Preprocess failed* status in the *Tasks* column, and no labeling task will be created for it.

When the conversion failed because of a temporary problem, project owners can retry it by clicking the retry icon next to the status. To retry multiple failed assets at once, select them, open the selected-assets menu, and click *Retry Preprocess*. Ango Hub does not show the retry action for permanent errors, such as unsupported or invalid DICOM files.

Ango Hub also retries temporary processing failures automatically during recovery checks. Permanent conversion errors are not retried automatically.

## Using the File Explorer Method

From the File Explorer, select the single DICOM files you'd like to group into a series, or select the folder containing the DICOM files. Then, enable the checkbox named "*Upload individual DICOM frames as single NRRD file*". Click on *Upload*.

To import several DICOM series at once, select multiple folders. Ango Hub treats each selected folder as a separate series and converts it into its own NRRD asset.


---

# 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/data/importing-assets/bundled-assets/importing-multiple-single-frame-dicom-files-as-a-3d-dicom-series.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.