# Whole adult woman body ct scan and mri?
**URL:** https://discourse.slicer.org/t/whole-adult-woman-body-ct-scan-and-mri/48054
**Category:** Support
**Tags:** dicom
**Created:** [September 3, 2026, 11:55am UTC](https://discourse.slicer.org/t/whole-adult-woman-body-ct-scan-and-mri/48054 "2026-09-03T11:55:27Z")
**Posts on this page:** 5
**Page:** 1
### Author:  [@Melodicpinpon](https://discourse.slicer.org/u/Melodicpinpon)
#### Post date: [September 3, 2026, 11:55am UTC](https://discourse.slicer.org/t/whole-adult-woman-body-ct-scan-and-mri/48054/1 "2026-09-03T11:55:27Z")
Hi everyone,
Can anyone please tell me where I could download a whole (young healthy) adult woman body ct scan and mri?
I would be used to start building a libre 3D atlas of the woman’s anatomy.
---
### Author:  [@aiden.zhu](https://discourse.slicer.org/u/aiden.zhu)
#### Post date: [September 3, 2026, 9:20pm UTC](https://discourse.slicer.org/t/whole-adult-woman-body-ct-scan-and-mri/48054/2 "2026-09-03T21:20:59Z")
Not really sure which one might get you there, but it seems worth taking a check from the following sites;
[The Visible Human Project - Getting the Data](https://www.nlm.nih.gov/research/visible/getting_data.html#:~:text=The%20anatomical%20cross-sections%20are%20also%20at%201,dataset%20is%20about%2040%20gigabytes%20in%20size).
> **[HEALTHY-TOTAL-BODY-CTS - The Cancer Imaging Archive (TCIA)](https://www.cancerimagingarchive.net/collection/healthy-total-body-cts/#:~:text=You%20are%20leaving%20TCIA%20*%20About%20the,*%20About%20the%20Cancer%20Imaging%20Program%20(CIP))**
> **[Total-Body \[18F\]FDG-PET/CT Imaging of Healthy Controls: Test/Retest Data for...](https://zenodo.org/records/16588733)**
>
> This dataset comprises CT and PET scans, along with the corresponding segmentations, of 48 healthy Caucasian subjects from a Siemens Biograph Vision QUADRA.
> **[Dataset with segmentations of 117 important anatomical structures in 1228 CT...](https://zenodo.org/records/10047292)**
>
> Info: This is version 2 of the TotalSegmentator dataset.In 1228 CT images we segmented 117 anatomical structures covering a majority of relevant classes for most use cases. The CT images were randomly sampled from clinical routine, thus representing...
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### Author:  [@fedorov](https://discourse.slicer.org/u/fedorov)
#### Post date: [September 3, 2026, 9:54pm UTC](https://discourse.slicer.org/t/whole-adult-woman-body-ct-scan-and-mri/48054/3 "2026-09-03T21:54:14Z")
If you are looking for Visible Human, it is available from IDC: [https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection\_id=nlm&collection\_id=nlm\_visible\_human\_project](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=nlm&collection_id=nlm_visible_human_project)
Best way to get started with IDC is via agentic interfaces described here: [Start here | IDC User Guide](https://learn.canceridc.dev/ai-assistants/agents)
---
### Author:  [@Melodicpinpon](https://discourse.slicer.org/u/Melodicpinpon)
#### Post date: [September 8, 2026, 8:24am UTC](https://discourse.slicer.org/t/whole-adult-woman-body-ct-scan-and-mri/48054/4 "2026-09-08T08:24:46Z")
The first link opens another website and contains 135 files for 30 patients. There is no way to filter by sex or to previsualize the content. I chose the first dataset of the list, put it in my ‘cart’ and have to choose wich serie to download (again without previsualization).
I am again downloading 23 Gb of data crossing my fingers to be lucky and find a whole body of adult woman…
Edit: 40 minutes later, I have 1228 folders containing about 100 segmentations each.
I only need a CT scan and an MRI of an adult woman…
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### Author:  [@fedorov](https://discourse.slicer.org/u/fedorov)
#### Post date: [September 8, 2026, 1:51pm UTC](https://discourse.slicer.org/t/whole-adult-woman-body-ct-scan-and-mri/48054/5 "2026-09-08T13:51:50Z")
I am not sure what you are referring to by “the first link”, and I don’t know what is the screenshot that you included. But if you use IDC Portal, you can visualize and download individual series, see tutorial slides here: [Portal tutorial | IDC User Guide](https://learn.canceridc.dev/tutorials/portal-tutorial).
As I mentioned earlier, the easiest is to set up your LLM agent with IDC skill/MCP. Here’s the response on how to download Visible Human data from IDC: [Claude](https://claude.ai/share/9e3611f2-91d4-47c2-a788-a3e391026d63) (the actual response is below for completeness).
Happy to respond to any questions about getting data from IDC. We also have dedicated IDC user forum here: [https://discourse.canceridc.dev/](https://discourse.canceridc.dev/).
* * *
# Listing and Downloading Visible Human Modalities from IDC
The Visible Human Project is in the NCI Imaging Data Commons as collection `nlm_visible_human_project` (2 subjects: `VHP-M` and `VHP-F`), on data release v24.
## What’s in the collection
| Modality | What it is | Series | Size |
| --- | --- | --- | --- |
| `CT` | Whole-body axial CT | 11 | ~2.1 GB |
| `MR` | T1/T2, axial and coronal, by body region | 24 | ~0.25 GB |
| `XC` | Digitized cryosection photographs (70mm film + full-color direct digital) | 4 | ~303 GB |
Note the size skew — `XC` is 97% of the collection, so download it deliberately rather than by accident.
## Setup
```auto
pip install idc-index
```
## 1. List what’s available
```auto
from idc_index import IDCClient
client = IDCClient()
client.sql_query("""
SELECT Modality, PatientID, SeriesDescription, SeriesInstanceUID,
ROUND(series_size_MB, 1) AS size_MB
FROM index
WHERE collection_id = 'nlm_visible_human_project'
ORDER BY Modality, PatientID, SeriesDescription
""")
```
A modality-level summary first, if you just want the shape of it:
```auto
client.sql_query("""
SELECT Modality,
COUNT(DISTINCT SeriesInstanceUID) AS series,
ROUND(SUM(series_size_MB)/1024, 2) AS size_GB
FROM index
WHERE collection_id = 'nlm_visible_human_project'
GROUP BY Modality
""")
```
No-install alternative, same data over REST:
```auto
curl -s https://api.imaging.datacommons.cancer.gov/v3/sql \
-H 'content-type: application/json' \
-d '{"sql":"SELECT Modality, COUNT(DISTINCT SeriesInstanceUID) n FROM index WHERE collection_id = '\''nlm_visible_human_project'\'' GROUP BY 1"}'
```
## 2. Download one modality
`download_from_selection` takes `downloadDir` first and filter keywords after — this trips people up because the sibling method `download_dicom_series` reverses that order.
```auto
# All CT (~2.1 GB)
client.download_from_selection(
downloadDir="./vhp/ct",
collection_id="nlm_visible_human_project",
seriesInstanceUID=list(client.sql_query("""
SELECT SeriesInstanceUID FROM index
WHERE collection_id = 'nlm_visible_human_project' AND Modality = 'CT'
""")['SeriesInstanceUID'].values)
)
```
Swap `'CT'` for `'MR'` or `'XC'`. To narrow further, add `AND PatientID = 'VHP-M'`, or filter on `SeriesDescription LIKE 'T2%'` for just the T2 MR series.
Files land as `.dcm` under a `%collection_id/%PatientID/%StudyInstanceUID/%Modality_%SeriesInstanceUID` tree; the real DICOM UIDs live inside the file headers, not the filenames.
From the shell instead:
```auto
idc download --download-dir ./vhp/ct
```
## 3. Or pull directly from S3
Every series has a public `series_aws_url`. With `s5cmd` installed:
```auto
# get the URLs
curl -s https://api.imaging.datacommons.cancer.gov/v3/cohort/manifest.txt \
-H 'content-type: application/json' \
-d '{"filters":{"terms":{"collection_id":["nlm_visible_human_project"],"Modality":["MR"]}}}' \
-o vhp_mr_manifest.txt
# fetch them
cat vhp_mr_manifest.txt | xargs -I {} s5cmd --no-sign-request cp "{}" ./vhp/mr/
```
No credentials, no egress charges. Add `--endpoint-url https://storage.googleapis.com` if you’d rather pull from GCS.
## Before you preview or publish
Browse a single series without downloading via `client.get_viewer_URL(seriesInstanceUID=uid)`, which opens OHIF in a browser.
On licensing: this collection is not CC-BY like most of IDC. All 39 series carry the National Library of Medicine Terms and Conditions (May 21, 2019). A license is no longer required for access, but NLM asks that you not imply their endorsement of anything you build. Generate attributions with `client.citations_from_selection(collection_id="nlm_visible_human_project")`.
* * *
Metadata current as of IDC data release v24 (`idc-index-data` 24.2.2).