Stella X. Yu : Papers / Google Scholar

High Fidelity Direct-Contrast Synthesis from Magnetic Resonance Fingerprinting in Diagnostic Imaging
Ke Wang and Mariya Doneva and Thomas Amthor and Vera C. Keil and Ekin Karasan and Fei Tan and Jonathan I. Tamir and Stella X. Yu and Michael Lustig
Summa Cum Laude Award, International Society for Magnetic Resonance in Medicine, Online, 8-14 August 2020

MR Fingerprinting is an emerging attractive candidate for multi-contrast imaging since it quickly generates reliable tissue parameter maps. However, contrast-weighted images generated from parameter maps often exhibit artifacts due to model and acquisition imperfections. Instead of direct modeling, we propose a supervised method to learn the mapping from MRF data directly to synthesized contrast-weighted images, i.e., direct contrast synthesis (DCS). In-vivo experiments on both volunteers and patients show substantial improvements of our proposed method over previous DCS method and methods that derive synthetic images from parameter maps.

MR fingerprinting, deep learning, MR contrast synthesis