# Clinical Data Onboarding Guide

Generated: 2025-09-06T00:13:54.227235

## Overview

This guide helps you onboard clinical imaging data for AI-powered segmentation.

## Data Requirements

### Supported Formats
- **DICOM**: Medical imaging standard format
- **NIfTI**: Neuroimaging Informatics Technology Initiative format

### Modalities
- **MRI**: T1, T1c, T2, FLAIR sequences
- **CT**: Single or multi-phase imaging

### Quality Requirements
- **Spatial Resolution**: Minimum 1mm isotropic
- **Image Size**: 128x128x128 or larger recommended
- **Orientation**: Standard neurological orientation
- **Intensity**: Proper windowing and contrast

## Preparation Steps

### 1. DICOM to NIfTI Conversion
If your data is in DICOM format:
```bash
# Using dcm2niix
dcm2niix -o output_directory input_dicom_directory

# Using MONAI
python scripts/data/convert_dicom_to_nifti.py --input dicom_dir --output nifti_dir
```

### 2. Data Organization
Organize your data in the clinical inbox:
```
data/clinical_inbox/
├── patient_001/
│   ├── t1.nii.gz
│   ├── t1c.nii.gz
│   ├── t2.nii.gz
│   └── flair.nii.gz
├── patient_002/
│   └── ... (same structure)
```

### 3. Quality Checks
- Verify image orientation
- Check spatial alignment between modalities
- Ensure proper intensity scaling

## Processing Pipeline

### 1. Run Clinical Inference
```bash
./scripts/clinical/run_clinical_inference.sh
```

### 2. Review Results
Results will be saved to:
- `reports/clinical_exports/`: Segmentation masks
- `reports/clinical_exports/overlays/`: Visualization overlays
- `reports/clinical_exports/reports/`: Clinical reports

### 3. Quality Assurance
- Review overlays for accuracy
- Validate against clinical ground truth
- Document any issues or corrections needed

## Clinical Workflow Integration

### PACS Integration
- Configure DICOM endpoints
- Set up automated data routing
- Implement result reporting

### 3D Slicer Integration
- Load segmentation results
- Review in clinical context
- Export for clinical reporting

## Safety and Compliance

### Validation
- Always validate AI results clinically
- Use multiple modalities for confirmation
- Follow institutional protocols

### Documentation
- Maintain audit trail
- Document model version and parameters
- Record clinical review decisions

## Support

For technical support or clinical questions, contact the development team.
