Configuration Reference

HABIT uses YAML to control each pipeline step. Example templates live under the repository config/ directory (catalog: Configuration recipe catalog).

Usage: copy a template → edit data_dir / out_dir in the #%%==== blocks → run the corresponding habit command.

Omitted keys use program defaults (listed on each page below). Example values in templates are for reference only.

Note

If you only pip install habit without the config/ directory, obtain the full source tree from GitHub.

• Configuration recipe catalog
  • By workflow
  • Starter demos
  • Field reference pages
• Preprocessing Configuration
  • Preprocessing configuration parameters
  • DICOM sort configuration (habit sort-dicom)
• DICOM Sort Configuration
  • Top-level fields
  • Notes
• Habitat Segmentation Configuration
  • Habitat Analysis Configuration Parameters
• Feature Extraction Configuration
• Traditional Radiomics Configuration
  • paths
  • processing
  • export
  • logging
  • Backward-compatible flat keys
  • PyRadiomics parameter YAML
• Machine Learning Configuration
  • Machine learning configuration parameters
  • Model comparison (habit compare)
• Model Comparison Configuration
  • Top-level fields
  • Typical outputs under output_dir
• Auxiliary Tools and Data Configuration
  • Data configuration parameters
  • ICC analysis configuration (habit icc)
  • Test-Retest configuration (habit retest)
  • Traditional radiomics CLI configuration (habit radiomics)
  • Repository configuration template index
  • Configuration file validation
  • FAQ