561-01-010 ISMRM Abstract

Synthetic STIR Sequences Offer Same Edema Contrast as Standard-of-Care Acquisitions

Primary: Analysis Methods - Image Synthesis and Translation

Secondary: Neuro - Spinal Cord

561-01-010 · Generative Models for Image Synthesis · Wednesday, 13 May, 8:20 AM–9:15 AM · Digital Posters Row B

Keywords: Image synthesis Edema Spine Fat suppression STIR

Accepted

Thomas C Arnold¹, Long Wang¹, Ajit Shankaranarayanan¹, Lawrence Tanenbaum²

¹Subtle Medical Inc, Menlo Park, United States of America

²DRT Consulting, Riverside, United States of America

Presenting Author: Zechen Zhou

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References

1. Tanenbaum, L. N., et al. "Deep Learning–Generated Synthetic MR Imaging STIR Spine Images Are Superior in Image Quality and Diagnostically Equivalent to Conventional STIR: A Multicenter, Multireader Trial." American Journal of Neuroradiology 44.8 (2023): 987-993. DOI: 10.3174/ajnr.A7920 [doi]

2. Kim, Sewon, et al. "Deep‐learned short tau inversion recovery imaging using multi‐contrast MR images." Magnetic Resonance in Medicine 84.6 (2020): 2994-3008. DOI: 10.1002/mrm.28327 [doi]

3. Haubold, Johannes, et al. "Generating virtual short tau inversion recovery (STIR) images from T1-and T2-weighted images using a conditional generative adversarial network in spine imaging." Diagnostics 11.9 (2021): 1542. DOI: 10.3390/diagnostics11091542 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/561-01-010