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KomaMRI.jl: An open-source framework for general MRI simulations with GPU acceleration.

Carlos Castillo-Passi1,2,3, Ronal Coronado2,3,4, Gabriel Varela-Mattatall5,6

  • 1School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

Magnetic Resonance in Medicine
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Koma, a new MRI simulation framework, offers high performance and ease of use for researchers and educators. It provides accurate, fast simulations for developing novel MRI techniques and training machine learning models.

Keywords:
Bloch equationsGPUGUIJuliaopen sourcesimulation

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Area of Science:

  • Medical Imaging
  • Computational Science

Background:

  • Magnetic Resonance Imaging (MRI) simulations are crucial for developing new techniques and understanding image formation.
  • Existing MRI simulators may lack performance, ease of use, or extensibility.

Purpose of the Study:

  • To develop Koma, an open-source, high-performance, user-friendly, and extensible MRI simulation framework.
  • To enable cross-platform and general use for diverse MRI research applications.

Main Methods:

  • Koma is built using the Julia programming language, leveraging CPU and GPU parallelization to solve Bloch equations.
  • It accepts Pulseq-compatible pulse sequences and scanner parameters, storing raw data in ISMRMRD format.
  • A web-based graphical user interface and integration with MRIReco.jl for reconstruction are included.

Main Results:

  • Koma demonstrated high accuracy, with mean absolute differences below 0.1% compared to JEMRIS.
  • It exhibited superior GPU performance compared to MRiLab and was eight times faster than JEMRIS on personal computers.
  • Usability testing showed Koma to be easy to use, with 65% of students recommending it.

Conclusions:

  • Koma's speed and flexibility enhance accessibility for MRI education and research.
  • It is suitable for designing and testing novel pulse sequences using Pulseq files.
  • Koma can generate synthetic data for training machine learning models in medical imaging.