Overview
Voyager Labs Data Quality provides advanced tools for assessing and improving the quality of your CT scan data. These experimental features offer comprehensive metrics, automated quality checks, and recommendations to help you achieve optimal scan results.What is Data Quality Assessment?
Data quality assessment in Voyager Labs includes:- Automated quality metrics for scan evaluation
- AI-powered defect detection and classification
- Comparative analysis against quality standards
- Recommendations for scan optimization
Key Features
Quality Metrics
Noise Assessment
- Signal-to-noise ratio (SNR) analysis
- Noise distribution mapping across the scan volume
- Temporal noise evaluation for time-series data
- Spatial frequency analysis
Resolution Analysis
- Spatial resolution measurement
- Contrast resolution assessment
- Edge sharpness evaluation
- Modulation transfer function (MTF) calculation
Artifact Detection
- Beam hardening artifact identification
- Ring artifacts detection and quantification
- Motion artifacts assessment
- Streak artifacts analysis
AI-Powered Analysis
Automated Quality Scoring
- Overall quality score (0-100 scale)
- Component-specific scores for different quality aspects
- Comparative ranking against similar scans
- Trend analysis over multiple scans
Defect Classification
- Artifact type identification
- Severity level assessment
- Impact analysis on downstream processing
- Remediation suggestions
Getting Started
Prerequisites
- Access to Voyager Labs
- Scanned data ready for analysis
- Basic understanding of CT scan quality parameters
Running Quality Assessment
- Select your data in Voyager Labs
- Navigate to Data Quality section
- Choose assessment type (comprehensive, quick, or custom)
- Configure parameters for your specific needs
- Run the analysis and review results
Assessment Types
Quick Assessment
- Basic quality metrics in under 2 minutes
- Essential quality indicators only
- Suitable for routine quality checks
Comprehensive Assessment
- Full quality analysis (5-15 minutes)
- All available metrics and AI analysis
- Detailed recommendations and reports
- Suitable for critical scans or research
Custom Assessment
- User-defined parameters and thresholds
- Specific metric selection
- Custom quality criteria
- Suitable for specialized applications
Understanding Results
Quality Score Interpretation
Excellent (90-100)
- Scan meets or exceeds industry standards
- Minimal artifacts or noise
- Optimal for all downstream analysis
Good (70-89)
- Scan quality is acceptable for most applications
- Minor artifacts present but manageable
- May require some preprocessing
Fair (50-69)
- Scan quality is marginal
- Noticeable artifacts or noise
- Requires preprocessing or rescanning
Poor (0-49)
- Scan quality is inadequate
- Significant artifacts or noise
- Rescanning recommended
Detailed Metrics
Noise Metrics
- SNR values by region
- Noise distribution maps
- Temporal stability indicators
Resolution Metrics
- Spatial resolution measurements
- Contrast detail curves
- Edge response functions
Artifact Analysis
- Artifact location and extent
- Severity classification
- Impact assessment
Best Practices
Pre-Scan Optimization
- Proper sample preparation and positioning
- Optimal scan parameters selection
- Environmental control (vibration, temperature)
- Equipment calibration verification
Post-Processing
- Artifact correction when possible
- Noise reduction techniques
- Resolution enhancement methods
- Quality validation after processing
Quality Monitoring
- Regular quality assessments for trending
- Baseline establishment for your applications
- Quality control procedures
- Documentation of quality metrics
Troubleshooting
Common Quality Issues
High Noise Levels
- Check scan parameters (exposure time, current)
- Verify sample positioning and stability
- Consider environmental factors
- Review detector calibration
Poor Resolution
- Optimize scan geometry
- Check reconstruction parameters
- Verify sample size and positioning
- Review detector settings
Artifact Problems
- Identify artifact sources
- Adjust scan parameters
- Improve sample preparation
- Consider alternative scan strategies
Performance Optimization
- Use appropriate assessment type for your needs
- Close unnecessary applications during analysis
- Consider data size limitations
- Monitor system resources
Advanced Features
Batch Processing
- Multiple scan analysis in sequence
- Quality trend analysis over time
- Comparative studies between scans
- Automated reporting generation
Custom Metrics
- User-defined quality criteria
- Application-specific thresholds
- Custom scoring algorithms
- Integration with external tools
Export and Reporting
- Detailed quality reports in PDF format
- Metric data export for external analysis
- Visualization exports for presentations
- Integration with quality management systems