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Abstract #1964

MRtwin: an open-source Python package to create virtual qMRI phantoms for benchmark and synthetic data generation

Matteo Cencini1,2, Marta Lancione3, Laura Biagi3, Alessandra Retico1, and Michela Tosetti3
1INFN, Pisa Division, Pisa, Italy, 2Imago7 Foundation, Pisa, Italy, 3IRCCS Stella Maris, Pisa, Italy

Synopsis

Keywords: Software Tools, Software Tools

Motivation: Developing new MR acquisition and reconstruction techniques requires data for testing, benchmarking, and, for deep-learning approaches, training. Digital twins help meet this need. While some frameworks include phantom generation routines, no dedicated, comprehensive package exists, especially for quantitative MR (qMRI).

Goal(s): To provide a lightweight, user-friendly tool for generating virtual phantoms for benchmarking and neural network training.

Approach: Our framework includes routines for generating virtual objects (e.g., numerical and brain-like phantoms), field inhomogeneities, coil sensitivities, gradient imperfections, and motion patterns.

Results: Our package produces realistic MR parameter distributions and field maps, validated by simulating a multi-echo SPGR dataset.

Impact: MRTwin represents a useful tool for sequence design, reconstruction optimization and benchmarking, by providing a framework for the generation of digital twins for quantitative imaging.

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Keywords