About

Cloud MR

Cloud MR is multi-year project aimed at developing a comprehensive software platform to simulate all aspects of the MRI experiment. By means of an intuitive web-based user interface, Cloud MR will allow the development of RF coils, pulse sequences and image reconstruction methods within an interconnected simulation environment that will enable users to optimize them jointly or individually.

Documentation and Code

User manuals and video tutorials will be available in the future through this website. Code is available as open source here.

Collaborate with Us

Contact us if you are interested in integrating your MRI toolbox into the Cloud MR framework.

Acknowledgement

The frontend of Cloud MR is based on HTML 5, JavaScript, and CSS 3, using Vue.js/React.js, PhP and MySQL with Laravel for the backend. Several people have contributed to the Cloud MR project, including: Giuseppe Carluccio, Tobias Block, Roy Wiggins, Jean-Claude Franchitti, Jordan Starcher, Alex Mammadov, Adam Rubens, August Gresens.

Funding

This research project is supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) of the National Institutes of Health (NIH) under the Awards R01 EB024536 and P41 EB017183. The content of this website is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

References

  • Montin E, Carluccio G, Collins C and Lattanzi R, A web-accessible tool for temperature estimation from SAR simulations (TESS) ; 30th Scientific Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM). London (UK), 07-12 May 2022, p. 582.
  • Montin E, Deniz CM, Cantarelli Rodrigues T, Gyftopoulos S, Kijowski R and Lattanzi R, Automatic Segmentation Of The Hip Bony Structures On 3D Dixon MRI Datasets Using Transfer Learning From A Neural Network Developed For The Shoulder ; 30th Scientific Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM). London (UK), 07-12 May 2022, p. 1412.
  • Montin E, Georgakis IP, Zhang B and Lattanzi R, A software tool to assess radiofrequency coil designs with respect to ultimate intrinsic performance limits ; 30th Scientific Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM). London (UK), 07-12 May 2022, p. 2780.
  • Montin E, Carluccio G and Lattanzi R, A web-accessible tool for rapid analytical simulations of MR coils via cloud computing ; 29th Scientific Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM). Virtual Conference, 15-20 May 2021, p. 3756.
  • Montin E, Carluccio G, Collins C and Lattanzi R, CAMRIE – Cloud-Accessible MRI Emulator ; 28th Scientific Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM). Virtual Conference, 08-14 August 2020, p. 1037.
  • Montin E, Wiggins R, Block KT and Lattanzi R, MR Optimum – A web-based application for signal-to-noise ratio evaluation ; 27th Scientific Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM). Montreal (Canada), 11-16 May 2019, p. 4617.

Publications using Cloud MR

  • Montin E and Lattanzi R , Seeking a widely adoptable practical standard to estimate signal-to-noise ratio in magnetic resonance imaging for multiple-coil reconstructions; Journal of Magnetic Resonance Imaging, vol 54(6), 2021, p. 1952-1964. DOI: 10.1002/jmri.27816