sirf-config 0.1.0

Configuration management for SIRF SPECT/PET reconstruction workflows

SIRF Config

A Python package for managing scanner and reconstruction configurations for SIRF SPECT/PET workflows.

Features

• Centralized Configuration: Manage scanner specifications, radionuclide properties, and reconstruction protocols in YAML files
• Type Safety: Full type hints and validation for configuration parameters
• Extensible: Easy to add new scanners, radionuclides, and protocols
• SIRF Integration: Drop-in replacement for manual parameter management in SIRF workflows
• Default Configurations: Includes configurations for common scanners (GE Discovery, Mediso AnyScan Trio)

Quick Start

Installation

pip install sirf-config

Basic Usage

from sirf_config import get_y90_spect_params, ConfigLoader

# Quick Y-90 SPECT reconstruction parameters
params = get_y90_spect_params('ge_670', '/path/to/data')
print(params)
# {'data_path': '/path/to/data', 'num_subsets': 12, 'num_epochs': 5, 
#  'resolution_model': (1.68, 0.03, False), 'smoothing_kernel': (6.8, 6.8, 6.8)}

# Advanced configuration management
config = ConfigLoader()
available_scanners = config.list_scanners()
protocol_config = config.get_protocol_config('y90_mediso_spect')

Command Line Usage

Create a user configuration template:

python -m sirf_config.utils --create-template ./my_configs

Validate configuration files:

python -m sirf_config.utils --validate ./my_configs

List available configurations:

python -m sirf_config.utils --list-configs

Supported Scanners

The package includes default configurations for:

SPECT Scanners

• GE Discovery 670: ge_discovery_670
• Mediso AnyScan Trio: mediso_anyscan_trio_spect

PET Scanners

• GE Discovery 690: ge_discovery_690
• Mediso AnyScan Trio: mediso_anyscan_trio_pet

Radionuclides

• Yttrium-90: y90 (bremsstrahlung imaging)

Configuration Structure

The package uses three YAML configuration files:

1. scanners.yaml: Scanner technical specifications
2. radionuclides.yaml: Radionuclide properties
3. protocols.yaml: Pre-configured scanner+radionuclide combinations

Example Scanner Configuration

scanners:
  ge_discovery_670:
    name: "GE Discovery 670"
    modality: "SPECT"
    psf:
      sigma_0: 1.68  # mm
      alpha: 0.03
      full_3d: false
    bremsstrahlung:
      smoothing_fwhm: [6.8, 6.8, 6.8]  # mm isotropic
    default_params:
      num_subsets: 12
      num_epochs: 2

Integration with SIRF Scripts

SPECT Reconstruction

#!/usr/bin/env python3
import argparse
from sirf_config import get_y90_spect_params
from sirf.STIR import *

parser = argparse.ArgumentParser()
parser.add_argument('--scanner', type=str, help='Scanner: ge_670, mediso')
parser.add_argument('--data_path', type=str, required=True)
args = parser.parse_args()

# Get configuration parameters
params = get_y90_spect_params(args.scanner, args.data_path)

# Use in SIRF reconstruction
spect_mat = SPECTUBMatrix()
spect_mat.set_resolution_model(*params['resolution_model'])
# ... rest of reconstruction

PET Reconstruction

from sirf_config import get_y90_pet_params

params = get_y90_pet_params('ge_690', '/path/to/data')
gauss = SeparableGaussianImageFilter()
gauss.set_fwhms(params['psf_kernel'])

Adding Custom Configurations

1. Create Custom Configuration Directory

from sirf_config import create_user_config_template

config_dir = create_user_config_template('./my_custom_configs')

2. Edit Configuration Files

Add your scanner to scanners.yaml:

scanners:
  my_custom_scanner:
    name: "My Custom Scanner"
    modality: "SPECT"
    psf:
      sigma_0: 1.5
      alpha: 0.025
      full_3d: false
    default_params:
      num_subsets: 16
      num_epochs: 3

Add a protocol to protocols.yaml:

protocols:
  y90_my_custom_spect:
    scanner: "my_custom_scanner"
    radionuclide: "y90"
    description: "Y-90 SPECT on My Custom Scanner"
    reconstruction_params:
      num_subsets: 16
      num_epochs: 5
      resolution_model: [1.5, 0.025, false]
      smoothing_kernel: [7.0, 7.0, 7.0]

3. Use Custom Configurations

from sirf_config import ConfigLoader

config = ConfigLoader('./my_custom_configs')
params = config.get_reconstruction_params('y90_my_custom_spect')

API Reference

Core Classes

• ConfigLoader: Main configuration management class
• create_reconstruction_args(): Convert configurations to reconstruction parameters

Convenience Functions

• get_y90_spect_params(scanner, data_path): Quick Y-90 SPECT parameters
• get_y90_pet_params(scanner, data_path): Quick Y-90 PET parameters

Utilities

• get_default_config_dir(): Get path to package default configurations
• create_user_config_template(): Create user configuration template
• validate_config_files(): Validate configuration file syntax and structure

Development

Setting Up Development Environment

git clone https://github.com/yourusername/sirf-config.git
cd sirf-config
pip install -e ".[dev]"

Running Tests

pytest

Code Formatting

black src/
isort src/
flake8 src/

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Citation

If you use this package in your research, please cite:

@software{sirf_config,
  title={SIRF Config: Configuration Management for SIRF Workflows},
  author={Your Name},
  year={2025},
  url={https://github.com/yourusername/sirf-config}
}

Acknowledgments

• Built for use with SIRF (Synergistic Image Reconstruction Framework)
• Supports medical imaging workflows for SPECT and PET reconstruction