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Gadgetron: an open source framework for medical image reconstruction.

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TLDR
This work presents a new open source framework for medical image reconstruction called the Gadgetron, which 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.
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, 2013. © 2012 Wiley Periodicals, Inc.

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Simultaneous multislice (SMS) imaging techniques

TL;DR: The relationship between classic parallel imaging techniques and SMS reconstruction methods is explored and the practical implementation of SMS imaging is described, including the acquisition of reference data, and slice cross‐talk.
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Compressed sensing for body MRI

TL;DR: An overview of the application of compressed sensing techniques in body MRI, where imaging speed is crucial due to the presence of respiratory motion along with stringent constraints on spatial and temporal resolution, is presented.
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Myocardial perfusion cardiovascular magnetic resonance: optimized dual sequence and reconstruction for quantification

TL;DR: A dual sequence for myocardial perfusion cardiovascular magnetic resonance and AIF measurement has been optimized for quantification of myocardia blood flow and reliable perfusion mapping was demonstrated and produced estimates with low variability.
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5D whole-heart sparse MRI.

TL;DR: A 5D whole‐heart sparse imaging framework is proposed for simultaneous assessment of myocardial function and high‐resolution cardiac and respiratory motion‐resolved whole‐ heart anatomy in a single continuous noncontrast MR scan.
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Non‐Cartesian parallel imaging reconstruction

TL;DR: This review will begin with an overview of non‐Cartesian k‐space trajectories and their sampling properties, followed by an in‐depth discussion of several selected non‐ Cartesian parallel imaging algorithms.
References
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TL;DR: It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients, and a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing.
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TL;DR: Practical incoherent undersampling schemes are developed and analyzed by means of their aliasing interference and demonstrate improved spatial resolution and accelerated acquisition for multislice fast spin‐echo brain imaging and 3D contrast enhanced angiography.
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The Design and Implementation of FFTW3

TL;DR: It is shown that such an approach can yield an implementation of the discrete Fourier transform that is competitive with hand-optimized libraries, and the software structure that makes the current FFTW3 version flexible and adaptive is described.
Journal ArticleDOI

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