Neurapedia - Neuroscience Imaging Pipeline

Neurapedia is a neuroscience-focused machine learning pipeline for brain imaging analysis, segmentation, and anomaly detection.

✅ Core Features

Neuroscience Pipeline

• Brain region segmentation: 10 color-coded regions
• Neuroimaging formats: NIfTI, DICOM (placeholder support)
• Anomaly detection: Statistical/ML-based detection
• Clinical reporting: Professional-grade reports
• Visualization support: Region mapping for 3D viewers

ML Models

• Brain tumor detection (CNN architecture planned)
• Anomaly classification
• fMRI activity prediction
• Segmentation models (nnU-Net integration)

📦 Project Structure

neurapedia/
├── src/
│   ├── neuroscience/      # Core neuroscience pipeline
│   ├── models/            # ML models
│   ├── api/               # FastAPI backend
│   └── utils/             # Utilities
├── notebooks/             # Jupyter notebooks
├── tests/                 # Unit tests
├── examples/              # Demo scripts
├── docs/                  # Documentation
└── requirements.txt

🔬 Brain Regions (10 Color-coded)

Region	Color	Function
Frontal Lobe	🔴 Red (#FF0000)	Decision making, Planning, Personality, Motor control
Parietal Lobe	🔵 Blue (#0000FF)	Touch, Sensory integration, Spatial awareness
Temporal Lobe	🟢 Green (#00FF00)	Hearing, Language, Memory
Occipital Lobe	🟡 Yellow (#FFFF00)	Vision, Visual processing
Cerebellum	🟣 Purple (#800080)	Coordination, Balance, Fine motor control
Brainstem	🟠 Orange (#FFA500)	Vital functions, Breathing, Heart rate
Hippocampus	🩷 Pink (#FF69B4)	Memory formation, Spatial navigation
Amygdala	🔴 Red-Orange (#FF4500)	Emotion, Fear response
Thalamus	💧 Teal (#00CED1)	Sensory relay, Consciousness
Basal Ganglia	🟢 Lime (#32CD32)	Motor control, Habit formation, Reward

🚀 Quick Start

cd ~/Desktop/neurapedia
pip install -r requirements.txt

# Run a demo
python examples/demo_neuroscience.py

# Run tests
python -m pytest tests/

🧠 Testing

Tests cover:

• Synthetic MRI generation
• Brain segmentation
• Anomaly detection
• Clinical report generation

python -m pytest tests/test_neuroscience.py -v

🧩 Segmentation Example

from src.neuroscience import BrainSegmenter
segmenter = BrainSegmenter()
mri_image = loader.load_nifti("synthetic")
segments = segmenter.segment_lobes(mri_image)
# Returns dict mapping region names to boolean masks

🩺 Clinical Reporting

Generates professional-grade reports for physician review:

from src.neuroscience import AnomalyDetector
detector = AnomalyDetector()
anomalies = detector.detect(mri_image)
report = detector.generate_clinical_report(anomalies)
# Includes: location, type, confidence, description, suggested actions

🌐 API (Planned)

FastAPI backend for:

• Neuroimaging upload endpoints
• Segmentation services
• Anomaly detection API
• Real-time 3D visualization support

🔗 Cloud Dataset Access

No large files stored locally - access datasets via:

• Human Connectome Project: https://www.humanconnectome.org/
• Allen Brain Atlas: https://portal.brain-map.org/
• Open Connectome Project: https://openconnecto.me/
• BrainGraph Database: https://braingraph.org/
• Allen Brain Cell Atlas: https://portal.brain-map.org/atlases-and-data/bkp/abcatlas

🧠 Neuroscience Context

Based on:

• ChatGPT conversation

🔮 Future Enhancements

1. Deep learning-based tumor detection
2. fMRI connectivity analysis
3. Multi-modal fusion (MRI + fMRI + EEG)
4. Real-time neuroimaging dashboard
5. Integration with clinical imaging devices

📜 License

MIT License - see LICENSE

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© 2026 Neurapedia Project | GitHub