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title: Jolia
emoji: 🫁
colorFrom: red
colorTo: gray
sdk: gradio
sdk_version: 6.22.0
app_file: app.py
short_description: Zero-shot CT findings with the Jolia 3D CT foundation model
python_version: "3.12"
startup_duration_timeout: 1h
pinned: false
license: other
---
# Jolia — zero-shot CT analysis
Demo of [`raidium/Jolia`](https://huggingface.co/raidium/Jolia), a 3D CT foundation model that
encodes a whole chest / abdominal CT volume into a global embedding **and** 102 named organ-query
embeddings, both aligned with radiology-report text.
Upload a NIfTI CT volume and:
- score free-text findings against the **whole volume** (global CLIP head), and
- route short findings phrases to a **single organ query** (ParallelOrganCLIP head, each organ with
its own trained temperature and bias).
The pipeline follows `example_zero_shot.py` from the model repo exactly: `JoliaPreprocessor`
(1.5 mm isotropic, 192³ centre crop, 11 CT windowing channels) for the image, and the paired
[`Qwen/Qwen3-Embedding-8B`](https://huggingface.co/Qwen/Qwen3-Embedding-8B) text encoder
(last-token pooling, context length 512) for the prompts.
> ⚠️ Research preview. Not a medical device; not for clinical use.
## Example volumes
The bundled example CTs come from the **TotalSegmentator dataset**
(Wasserthal et al., [Zenodo record 10047292](https://zenodo.org/records/10047292), **CC-BY-4.0**),
downloaded via [`YongchengYAO/TotalSegmentator-CT-Lite`](https://huggingface.co/datasets/YongchengYAO/TotalSegmentator-CT-Lite).
File names carry that dataset's own study-type / pathology metadata. Attribution:
> Wasserthal, J. et al. *TotalSegmentator: Robust segmentation of 104 anatomic structures in CT
> images.* Radiology: Artificial Intelligence (2023). Dataset licensed CC-BY-4.0.
## Notes
- Volumes are reoriented to the radiological axial layout (rows anterior→posterior, columns
right→left, slices inferior→superior) before `JoliaPreprocessor`, which then flips depth and
centre-crops.
- Probabilities are `sigmoid(calibrated logit)` — a per-pair "is this a match?" score, not a
softmax over prompts.
- DICOM series can be converted to NIfTI with `dcm2niix`.
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