tanya-akumu/selectGA

🤖 AI framework for gestational age estimation from blind sweep ultrasound videos in low-resource settings. Achieves 27% improvement in accuracy through adaptive frame selection. # SelectGA: Adaptive Frame Selection for Gestational Age Estimation from Blind Sweep Fetal Ultrasound Videos [ ] **SelectGA** is a novel AI framework designed to improve gestational age (GA) prediction from blind sweep ultrasound videos in low-resource healthcare settings. Our approach uses adaptive frame selection to identify the most clinically informative frames from ultrasound sweeps, achieving a **27% improvement** in prediction accuracy compared to existing methods. ## 🎯 Key Features - **Adaptive Frame Selection**: Intelligently identifies the most informative frames from blind sweep videos - **Anatomically-Guided Filtering**: Uses pretrained object detection to focus on frames containing fetal structures - **Diversity-Based Sampling**: Employs clustering to select diverse, non-redundant frames - **Resource-Efficient**: Designed specifically for low-resource healthcare environments - **Cross-Center Validation**: Tested across multiple geographical locations and equipment types ## 🚀 Performance Highlights - **9.60 days** Mean Absolute Error (MAE) - 27% improvement over baselines - **63.9%** of predictions within 7-day clinical threshold - **R² = 0.906** correlation with ground truth gestational age - Consistent performance across 2nd and 3rd trimesters - Validated on multi-center dataset from diverse resource settings ## 🛠️ Installation ### Prerequisites - Python 3.8+ - CUDA-capable GPU (recommended) - 16GB+ RAM ### Setup Environment ```bash # Clone the repository git clone github.com cd SelectGA # Create conda environment conda create -n selectga python=3.10 conda activate selectga # Install dependencies pip install -r requirements.txt ``` ## 📊 Dataset Our framework was validated on a multi-center fetal ultrasound dataset: - **1,314 blind sweep videos** from 162 study scans - **Two geographical centers** with different equipment (Philips Lumify, GE Voluson v8) - **245,048 total frames** across diverse gestatio …