Gadgetron: An open source framework for medical image reconstruction

TLDR

The framework is modality‑agnostic but is applied here to Cartesian and non‑Cartesian parallel MRI. This work introduces Gadgetron, an open‑source framework for medical image reconstruction. Gadgetron implements a dynamic, streaming data‑processing pipeline built from modular Gadgets, configurable at run‑time via an extensible markup language, with a plugin architecture that supports C/C++ and Python modules and includes GPU‑accelerated toolboxes for efficient reconstruction. Published in Magn Reson Med (2012).

Abstract

This work presents a new open source framework for medical image reconstruction called the “Gadgetron.” The framework implements a flexible system for creating streaming data processing pipelines where data pass through a series of modules or “Gadgets” from raw data to reconstructed images. The data processing pipeline is configured dynamically at run-time based on an extensible markup language configuration description. The framework promotes reuse and sharing of reconstruction modules and new Gadgets can be added to the Gadgetron framework through a plugin-like architecture without recompiling the basic framework infrastructure. Gadgets are typically implemented in C/C++, but the framework includes wrapper Gadgets that allow the user to implement new modules in the Python scripting language for rapid prototyping. In addition to the streaming framework infrastructure, the Gadgetron comes with a set of dedicated toolboxes in shared libraries for medical image reconstruction. This includes generic toolboxes for data-parallel (e.g., GPU-based) execution of compute-intensive components. The basic framework architecture is independent of medical imaging modality, but this article focuses on its application to Cartesian and non-Cartesian parallel magnetic resonance imaging. Magn Reson Med, 2012.