LUS-classification / README.md
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---
license: apache-2.0
datasets:
- alyaalmsouti/Pleural-Line-Segmentation-Masks
---
# Model Card
## Overview
This repository provides the trained models from:
**Hierarchy-Aware and Anatomy-Guided Learning for Lung Ultrasound Video Classification**
- Paper: https://arxiv.org/abs/2607.17551
- Code: https://github.com/Alya-Almsouti/LUS-video-classification
The models classify lung ultrasound videos into four classes:
1. Healthy
2. B-lines
3. Consolidations
4. B-lines with consolidations
## Available Models
| Model | Description |
|---|---|
| `baseline-vit-transformer` | ViT frame encoder with transformer-based temporal aggregation |
| `maskloss-block7-3heads` | Mask-guided attention loss applied to three heads at code block index 7 |
| `maskloss-block11-3heads` | Mask-guided attention loss applied to three heads at code block index 11 |
| `maskloss-block11-6heads` | Mask-guided attention loss applied to six heads at code block index 11 |
The implementation uses zero-based block indices. Therefore, code blocks `7` and `11` correspond to Blocks 8 and 12 in the paper.
## Model Files
Each model is distributed as a compressed `.zip` archive containing checkpoints and training outputs for all five patient-level cross-validation folds.
A typical archive contains:
```text
model-name/
β”œβ”€β”€ config.json
β”œβ”€β”€ final_metrics.json
β”œβ”€β”€ fold_0/
β”‚ β”œβ”€β”€ best.pt
β”‚ └── best_val_metrics.json
β”œβ”€β”€ fold_1/
β”œβ”€β”€ fold_2/
β”œβ”€β”€ fold_3/
└── fold_4/
```
Use `best.pt` as the selected checkpoint for each fold.
## Intended Use
These models are intended for research on lung ultrasound video classification and anatomy-guided deep learning.
They are not validated for clinical diagnosis or independent medical decision-making.
## Citation
Please cite the associated publication when using these models:
```bibtex
@article{almsouti2026hierarchy,
title = {Hierarchy-Aware and Anatomy-Guided Learning for Lung Ultrasound Video Classification},
author = {Almsouti, Alya and Mecharbat, Lotfi and Aboukhater, Noha and Alabrach, Yousef and Anwar, Siddiq and Kumar, Andre and Almakky, Ibrahim and Yaqub, Mohammad},
journal = {arXiv preprint arXiv:2607.17551},
year = {2026},
doi = {10.48550/arXiv.2607.17551}
}
```
## Contact
For questions, problems, or reproducibility issues, please open an issue in the GitHub repository.