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

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dc.catalogadorgjm
dc.contributor.authorCastillo Passi, Carlos
dc.contributor.authorCoronado, Ronal Manuel
dc.contributor.authorVarela Mattatall, Gabriel
dc.contributor.authorAlberola López, Carlos
dc.contributor.authorBotnar, René Michael
dc.contributor.authorIrarrázaval Mena, Pablo
dc.date.accessioned2024-01-30T15:23:31Z
dc.date.available2024-01-30T15:23:31Z
dc.date.issued2023
dc.description.abstractPurpose: To develop an open-source, high-performance, easy-to-use, extensible, cross-platform, and general MRI simulation framework (Koma). Methods: Koma was developed using the Julia programming language. Like other MRI simulators, it solves the Bloch equations with CPU and GPU parallelization. The inputs are the scanner parameters, the phantom, and the pulse sequence that is Pulseq-compatible. The raw data is stored in the ISMRMRD format. For the reconstruction, MRIReco.jl is used. A graphical user interface utilizing web technologies was also designed. Two types of experiments were performed: one to compare the quality of the results and the execution speed, and the second to compare its usability. Finally, the use of Koma in quantitative imaging was demonstrated by simulating Magnetic Resonance Fingerprinting (MRF) acquisitions. Results: Koma was compared to two well-known open-source MRI simulators, JEMRIS and MRiLab. Highly accurate results (with mean absolute differences below 0.1% compared to JEMRIS) and better GPU performance than MRiLab were demonstrated. In an experiment with students, Koma was proved to be easy to use, eight times faster on personal computers than JEMRIS, and 65% of test subjects recommended it. The potential for designing acquisition and reconstruction techniques was also shown through the simulation of MRF acquisitions, with conclusions that agree with the literature. Conclusions: Koma's speed and flexibility have the potential to make simulations more accessible for education and research. Koma is expected to be used for designing and testing novel pulse sequences before implementing them in the scanner with Pulseq files, and for creating synthetic data to train machine learning models.
dc.fechaingreso.objetodigital2024-06-04
dc.fuente.origenORCID
dc.identifier.doi10.1002/mrm.29635
dc.identifier.urihttps://doi.org/10.1002/mrm.29635
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/81072
dc.information.autorucInstituto de Ingeniería Biológica y Médica; Castillo Passi, Carlos; 0000-0001-6227-0477; 204150
dc.information.autorucEscuela de Ingeniería; Coronado, Ronal Manuel; 0000-0001-6735-2607; 1050234
dc.information.autorucEscuela de Ingeniería; Botnar, René Michael; 0000-0002-9447-4367; 1015313
dc.information.autorucInstituto de Ingeniería Biológica y Médica; Irarrázaval Mena, Pablo; 0000-0002-5186-2642; 57376
dc.language.isoen
dc.nota.accesoContenido completo
dc.rightsacceso abierto
dc.subjectBloch equations
dc.subjectGPU
dc.subjectGUI
dc.subjectJulia
dc.subjectOpen source
dc.subjectSimulation
dc.subject.ddc600
dc.subject.deweyTecnologíaes_ES
dc.titleKomaMRI.jl: An open‐source framework for general MRI simulations with GPU acceleration
dc.typeartículo
sipa.codpersvinculados204150
sipa.codpersvinculados1050234
sipa.codpersvinculados1015313
sipa.codpersvinculados57376
sipa.trazabilidadORCID;2024-01-15
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