Traditional Radiomics Configuration

This page documents the traditional whole-ROI radiomics workflow (habit radiomics). It is separate from habitat voxel / supervoxel radiomics configured under Habitat Segmentation Configuration.

Demo: config/radiomics/config_traditional_radiomics.yaml. PyRadiomics parameter presets live beside it (for example parameter.yaml) and as bundled defaults under habit/resources/radiomics/.

Command usage: Traditional radiomics.

Example configuration:

paths:
  # params_file optional: omit to use the bundled ROI preset
  # params_file: ./parameter.yaml
  images_folder: ../../demo_data/preprocessed/processed_images
  out_dir: ../../demo_data/results/radiomics_traditional

processing:
  n_processes: 2
  save_every_n_files: 5
  process_image_types:
    - delay2
    - delay3
    - delay5

export:
  export_by_image_type: true
  export_combined: true
  export_format: csv
  add_timestamp: false

logging:
  level: INFO
  console_output: true
  file_output: true

paths

  • images_folder (required): root that contains images/ and masks/ with matching <subject>/<modality>/ layout

  • out_dir (required): feature table output directory

  • params_file (optional): PyRadiomics parameter YAML; when omitted, HABIT uses the bundled ROI preset

processing

  • n_processes (default 2)

  • save_every_n_files (default 5): flush intermediate results every N files

  • process_image_types: modality folder names to process; null means all

  • target_labels: mask label IDs to extract (default [1])

export

  • export_by_image_type: write one table per modality

  • export_combined: also write a wide combined table

  • export_format: csv | json | pickle

  • add_timestamp: append a timestamp to output filenames

logging

  • level: DEBUG / INFO / …

  • console_output, file_output

Backward-compatible flat keys

Deprecated top-level aliases still accepted: params_file, images_folder, out_dir, n_processes (same meaning as the nested fields above).

PyRadiomics parameter YAML

Files such as config/radiomics/parameter.yaml follow the upstream PyRadiomics schema (imageType, featureClass, setting). Habitat voxel / supervoxel presets are documented under Habitat Segmentation Configuration and shipped in habit/resources/radiomics/.