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This review summarizes the existing techniques and methods used to generate synthetic contrasts from magnetic resonance imaging data focusing on musculoskeletal magnetic resonance imaging. To that end, the different approaches were categorized into 3 different methodological groups: mathematical image transformation, physics-based, and data-driven approaches. Each group is characterized, followed by examples and a brief overview of their clinical validation, if present. Finally, we will discuss the advantages, disadvantages, and caveats of synthetic contrasts, focusing on the preservation of image information, validation, and aspects of the clinical workflow.
Jean-Philippe Thiran, Friedhelm Christoph Hummel, Tobias Kober, Tom Hilbert, Erick Jorge Canales Rodriguez, Gabriel Girard, Elda Fischi Gomez, Marco Pizzolato, Gian Franco Piredda, Thomas Yu, Takuya Morishita, Elena Beanato, Alessandro Daducci, Maximilian Jonas Wessel, Chang-Hyun Park, Philipp Johannes Koch, Andéol Geoffroy Cadic-Melchior, Julia Brügger
Meritxell Bach Cuadra, Francesco La Rosa, Maxence Charles F Wynen, Benoît Macq