sirf-simind-connection 0.2.1

A wrapper for SIRF and SIMIND for Monte Carlo SPECT simulations

SIRF-SIMIND-Connection

A Python wrapper for SIRF and SIMIND integration for SPECT imaging.

Quick Links

• Full Documentation
• Installation

Key Features

• Monte Carlo SPECT Simulation
• Dual Scoring Routines (SCATTWIN/PENETRATE)
• DICOM to STIR Conversion
• Advanced Schneider2000 Density Conversion - Clinically validated HU-to-density mapping with 44 tissue segments

Installation

pip install sirf-simind-connection

Quick Start

from sirf_simind_connection import SimindSimulator, SimulationConfig
from sirf_simind_connection.configs import get
from sirf_simind_connection.utils.stir_utils import create_simple_phantom, create_attenuation_map

# Create phantom and attenuation map
phantom = create_simple_phantom()
mu_map = create_attenuation_map(phantom)

# Load pre-configured scanner settings
config = SimulationConfig(get("AnyScan.yaml"))
simulator = SimindSimulator(config, output_dir='output')

# Set inputs and run
simulator.set_source(phantom)
simulator.set_mu_map(mu_map)
simulator.set_energy_windows([126], [154], [0])  # Tc-99m ± 10%
simulator.run_simulation()

Advanced Density Conversion

from sirf_simind_connection.converters.attenuation import hu_to_density_schneider
import numpy as np

# Convert HU image to densities using Schneider2000 model
hu_image = np.array([[-1000, 0, 500], [800, 1200, 2000]])
density_map = hu_to_density_schneider(hu_image)  # 44-segment clinical model

Contributing

Please see our Contributing Guide.

License

Apache License 2.0