---
language: en
license: mit
tags:
- medical
- ultrasound
- lung
- segmentation
- classification
---

# Lung Ultrasound AI Model

## Model Description
Multi-task model for lung ultrasound analysis:
- Classification: COVID-19, Other Lung Disease, Healthy
- Segmentation: B-line detection and localization

## Architecture
- Encoder: EfficientNet-B3
- Decoder: SegFormer-style MLP
- Multi-task: Hard parameter sharing

## Training Data
- Classification: 1,062 images from Ugandan hospitals
- Segmentation: 401 images with B-line annotations

## Performance
| Metric | Value |
|--------|-------|
| Accuracy | 23.40% |
| Precision | 39.96% |
| Model Size | 44 MB |

## Usage
```python
import torch
from model import LungUltrasoundModel

model = LungUltrasoundModel()
model.load_state_dict(torch.load('pytorch_model.bin'))
model.eval()

# Preprocess image (224x224 RGB, normalized to 0-1)
# Run inference
class_logits, seg_logits = model(image_tensor)
```