README.md

---
title: README
emoji: 🔥
colorFrom: purple
colorTo: pink
sdk: static
pinned: false
---

# Lighter zoo x CT-FM: Through lighter zoo we provide several models pre-trained using the CT-FM vision foundation model for Computed Tomography (CT) scans.
CT-FM is a large-scale 3D image-based pre-trained model designed for diverse radiological tasks. The model was pre-trained on 148,000 CT scans from the Imaging Data Commons using label-agnostic contrastive learning.
## Model Details
The model demonstrates strong capabilities across multiple tasks:
- Whole-body multi-structure segmentation
- Heterogenous tumor segmentation across 4 anatomical sites
- Head CT triage
- Medical image retrieval 
- Semantic understanding of anatomical structures
Key features:
- Learns anatomical clustering without explicit labels
- Identifies similar anatomical structures across different scans
- Shows robustness in test-retest scenarios
- Provides interpretable salient regions in its embeddings

## Models Available
- Feature extractor `ct_fm_feature_extractor` which can be used for several feature-based tasks such as image retrieval, semantic search and outlier detection
- Fine-tuned whole body segmentation model `whole_body_segmentation` that segments 117 labels from the TotalSegmentator dataset
-  
## Installation
We provide pre-trained as well as fine-tuned models in the `lighter-zoo` package that interfaces with HF to provide easy to use APIs

To install the `lighter-zoo` package, use pip:
```bash
pip install lighter-zoo
```

Inspect specific models to see how you can interact with these