Open-source magnetic resonance imaging acquisition: Data and documentation for two validated pulse sequences
Gehua Tong,
Andreia S. Gaspar,
Enlin Qian,
Keerthi Sravan Ravi,
John Thomas Vaughan,
Rita G. Nunes,
Sairam Geethanath
Affiliations
Gehua Tong
Department of Biomedical Engineering, Columbia University in the City of New York, New York, NY, USA; Columbia Magnetic Resonance Research Center, Columbia University in the City of New York, New York, NY, USA
Andreia S. Gaspar
Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
Enlin Qian
Department of Biomedical Engineering, Columbia University in the City of New York, New York, NY, USA; Columbia Magnetic Resonance Research Center, Columbia University in the City of New York, New York, NY, USA
Keerthi Sravan Ravi
Department of Biomedical Engineering, Columbia University in the City of New York, New York, NY, USA; Columbia Magnetic Resonance Research Center, Columbia University in the City of New York, New York, NY, USA
John Thomas Vaughan
Department of Biomedical Engineering, Columbia University in the City of New York, New York, NY, USA; Columbia Magnetic Resonance Research Center, Columbia University in the City of New York, New York, NY, USA; Department of Radiology, Columbia University Irving Medical Center, Columbia University in the City of New York, New York, NY, USA
Rita G. Nunes
Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
Sairam Geethanath
Columbia Magnetic Resonance Research Center, Columbia University in the City of New York, New York, NY, USA; Corresponding author.
Raw data, simulated and acquired phantom images, and quantitative longitudinal and transverse relaxation times (T1/T2) maps from two open-source Magnetic Resonance Imaging (MRI) pulse sequences are presented in this dataset along with corresponding “.seq” files, sequence implementation scripts, and reconstruction/analysis scripts [1]. Real MRI data were collected from a 3T Siemens Prisma Fit and a 1.5T Siemens Aera via the Pulseq open-source MR sequence platform, and corresponding in silico data were generated using the simulation module of Virtual Scanner [2]. This dataset and its associated code can be used to validate the pipeline for using the same pulse sequences at other research sites using Pulseq, to provide guidelines for documenting and sharing open-source pulse sequences in general, and to demonstrate practical, customizable acquisition scripts using the PyPulseq library.
