A Modular End-to-End Open-Source Software Pipeline to Simulate the Entire MRI Experiment

Motivation: To democratize magnetic resonance (MR) imaging research by developing an open-source software simulation platform where researchers can test new technology, and radiologists can optimize clinical protocols without operating an actual MR scanner. Goal(s): To demonstrate the first comprehensive pipeline to simulate all stages of MR imaging experiments, from coil modeling to spin excitation and image reconstruction. Approach: Six open-source stand-alone software modules, implemented in various programming languages, were interconnected to simulate MR experiments using three head coils. Results: Realistic T1-weighted and T2-weighted brain MR images were successfully generated from the synthetic MR signal produced by a simulated spin-echo sequence. Impact: The comprehensive cloud-compatible simulation pipeline will make MR research freely accessible via internet. By enabling virtual experiments, this tool will allow users to generate synthetic data to train neural networks and will constitute a valuable tool for education and training.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/0943
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Modular End-to-End Open-Source Software Pipeline to Simulate the Entire MRI Experiment

Riccardo Lattanzi, Ilias I. Giannakopoulos, Anaïs Artiges, Eros Montin et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Advanced MRI Techniques and Applications
article

A Modular End-to-End Open-Source Software Pipeline to Simulate the Entire MRI Experiment

Riccardo Lattanzi, Ilias I. Giannakopoulos, Anaïs Artiges, Eros Montin, José E. Cruz Serrallés, Carlos Castillo‐Passi
article en

Abstract

Motivation: To democratize magnetic resonance (MR) imaging research by developing an open-source software simulation platform where researchers can test new technology, and radiologists can optimize clinical protocols without operating an actual MR scanner. Goal(s): To demonstrate the first comprehensive pipeline to simulate all stages of MR imaging experiments, from coil modeling to spin excitation and image reconstruction. Approach: Six open-source stand-alone software modules, implemented in various programming languages, were interconnected to simulate MR experiments using three head coils. Results: Realistic T1-weighted and T2-weighted brain MR images were successfully generated from the synthetic MR signal produced by a simulated spin-echo sequence. Impact: The comprehensive cloud-compatible simulation pipeline will make MR research freely accessible via internet. By enabling virtual experiments, this tool will allow users to generate synthetic data to train neural networks and will constitute a valuable tool for education and training.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 63%
Advanced MRI Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.