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AMIGOpy

Welcome to the AMIGOpy Documentation

This site documents the AMIGOpy software, including its main functionalities, coding standards, and development roadmap.

Note for developers
This documentation includes in-depth details about the source code, architecture, and contribution guidelines.
Regular users should focus on the pages describing the main features, user guides, and roadmap — no need to dive into implementation details unless you're contributing.

Overview

AMIGOpy is a medical imaging toolkit designed to support radiotherapy research and clinical workflows.

It provides tools for:

  • ⚡ Radiotherapy workflows — treatment planning, data handling, and advanced analysis
  • 🧩 Segmentation & Autocontouring — integrated with AI-based APIs and customizable pipelines
  • 🎲 Monte Carlo simulation — dose calculation, modeling, and validation for research and clinical applications
  • 🌐 3D / 4D Rendering — high-quality visualization for volumetric and time-resolved imaging data
  • 🧠 Research & Development — flexible tools for rapid prototyping, innovation, and integration with external platforms

AMIGOpy is designed to bring together automation, research tools, and clinical support into a single, extensible platform.
It not only provides built-in functionalities but also integrates and expands upon community-driven developments, creating a powerful and collaborative software ecosystem.

Documentation Structure

1. Installation

See Installation
Step-by-step instructions for installing both the compiled version and the developer setup.

2. Coding & Documentation Guidelines

See Software Documentation Guidelines
Clear standards for writing docstrings, using type hints, and maintaining consistent code style.
These rules are mandatory for all contributors.

3. Software Variables & Developer Notes

See General Variable Descriptions
An overview of variable naming conventions, data structures, and core architecture.

Key Features

AMIGOpy contains a wide array of tools and resources for medical physics and imaging research:

  • 📷 Supported File Formats:
    • Medical Images: Import, display, and manage standard DICOM, NIfTI (.nii/.nii.gz), MetaImage (.mha/.mhd), NumPy arrays (.npy), TIFF stacks, and IrIS formats.
    • 3D Printing & CAD: Import and visualize 3D meshes and CAD formats including STL, OBJ, 3MF, and STEP/STP.
  • 🕒 4DCT Analysis: Dynamic navigation through 4D computed tomography datasets, including 4DCT series comparisons, series splitting, and temporal video loop rendering.
  • 🧪 Dual Energy CT (DECT): Comprehensive calibration, extraction, and generation of Relative Electron Density (RED), Effective Atomic Number (Zeff), Zeff-vs-I-value, I-value, and Stopping Power Ratio (SPR) using multiple conversion methods.
  • 🎯 Treatment Plan Visualization: Full integration with radiotherapy DICOM (RT-DICOM) standards to import and overlay 3D RTDose distributions, RTStruct contours, and RTPlan Brachytherapy sources (including channel overlays, dwell times, and source positions).
  • 🔄 Image Registration: Support for both automatic image registration (intensity-based mutual registration) and manual rigid/translational registration for precise multi-scan alignment.
  • ✍️ Contours & Overlays: Advanced multi-layer overlays (up to 4 concurrent layers), interactive cylindrical ROI selection, contour generation, and dose-volume histogram (DVH) statistics.
  • 🛠️ 3D Printing & Phantom Design: Tissue-equivalent phantom design tools, including matching 3D printing filaments with specific tissue RED/Zeff values and G-code file parsing/splitting.

[!TIP] This is only a subset of the capabilities in AMIGOpy. There are many more features available in the software—we highly encourage you to explore the Documentation section of this site for detailed explanations and step-by-step user guides!