Gadgetron: An open source framework for medical image reconstruction

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...

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Bibliographic Details
Published in:	Magnetic resonance in medicine Vol. 69; no. 6; pp. 1768 - 1776
Main Authors:	Hansen, Michael Schacht, Sørensen, Thomas Sangild
Format:	Journal Article
Language:	English
Published:	Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.06.2013 Wiley Subscription Services, Inc
Subjects:	Algorithms GPU Image Enhancement - methods Image Interpretation, Computer-Assisted - methods image reconstruction Magnetic Resonance Imaging - methods open source Programming Languages Reproducibility of Results Sensitivity and Specificity Software Software Design
ISSN:	0740-3194, 1522-2594, 1522-2594
Online Access:	Get full text
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Summary:	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, 2013. © 2012 Wiley Periodicals, Inc.
Bibliography:	ArticleID:MRM24389 Disclosure: The National Heart, Lung, and Blood Institute and Siemens Medical Systems have a Cooperative Research and Development Agreement (CRADA). ark:/67375/WNG-KTN1NHTR-4 istex:4B39DE680448949FE17DBB512AD1CA8C434787EB Disclosure The National Heart, Lung, and Blood Institute and Siemens Medical Systems have a Cooperative Research and Development Agreement (CRADA). ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23
ISSN:	0740-3194 1522-2594 1522-2594
DOI:	10.1002/mrm.24389