DOI: 10.11606/t.76.2019.tde-06052019-103714
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PyMR: a framework for programming magnetic resonance systems

Abstract: Carlos , 2018. In recent years, the use of magnetic resonance technology has grown with advances in hardware, delivering accessible and small-size equipment and devices that open a range of new applications. Innovation in this field requires versatility and flexibility of both hardware and software. Despite the technological advances in the magnetic resonance hardware, the software still the most notable problem currently. This stagnation, delays progress that could reduce production costs and deliver faste… Show more

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Cited by 5 publications
(6 citation statements)
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“…This DMRS was interfaced to a 1.5T, 90‐cm magnet (Oxford Magnet Technology, Oxfordshire, UK) with a clinical gradient system (model SC72; Siemens, Erlangen, Germany). The DMRS software was created and controlled by Python Magnetic Resonance Framework, and the system has a specialized Integrated Development Environment and ToRM Console for creating MR sequences 30–34 . The magnet was initially designed to operate at 4 T, but was ramped down to 1.5 T without adjusting the passive shims of the system, leaving a relatively nonuniform B 0 .…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…This DMRS was interfaced to a 1.5T, 90‐cm magnet (Oxford Magnet Technology, Oxfordshire, UK) with a clinical gradient system (model SC72; Siemens, Erlangen, Germany). The DMRS software was created and controlled by Python Magnetic Resonance Framework, and the system has a specialized Integrated Development Environment and ToRM Console for creating MR sequences 30–34 . The magnet was initially designed to operate at 4 T, but was ramped down to 1.5 T without adjusting the passive shims of the system, leaving a relatively nonuniform B 0 .…”
Section: Methodsmentioning
confidence: 99%
“…The DMRS software was created and controlled by Python Magnetic Resonance Framework, and the system has a specialized Integrated Development Environment and ToRM Console for creating MR sequences. [30][31][32][33][34] The magnet was initially designed to operate at 4 T, but was ramped down to 1.5 T without adjusting the passive shims of the system, leaving a relatively nonuniform B 0 .…”
Section: In Vivo Validation Of the Me-free Sequencementioning
confidence: 99%
“…Phantom and in vivo human brain images were acquired as previously described by Torres et al 10 using a CIERMag digital MR spectrometer (DMRS) [19][20][21] interfaced to a 1.5T, 90-cm magnet (Oxford Magnet Technology) and a clinical gradient system (model SC72; Siemens). The magnet was designed for operation at 4T, but was ramped down to 1.5T without passive shim adjustment or higher order shimming, resulting in a relatively inhomogeneous B 0 .…”
Section: Methodsmentioning
confidence: 99%
“…Each Tx channel is capable of performing AM modulation in a 4‐quadrants approach, with amplitude dynamics of 16 bits, along with FM (24 bits‐0.373 Hz resolution) and phase‐modulated (14 bits‐0.088° resolution) capabilities. This digital MR spectrometer was interfaced to a 1.5 T, 90‐cm magnet (Oxford Magnet Technology, Oxfordshire, UK) with a clinical gradient system (model SC72, Siemens, Erlangen, Germany), using the software created and controlled by Python MR framework, using Python v3.8 19‐22 , a specialized integrated development environment for creating MR sequences, 19,22 and Tomografo de Ressonância Magnética‐Console 19,23 . The magnet was designed to operate at 4 T but was ramped down to 1.5 T without adjusting the passive shims, leaving a relatively nonuniform B 0 .…”
Section: Methodsmentioning
confidence: 99%