303-01-009 ISMRM Abstract

Deep Learning driven Inversion framework for shear Modulus estimation in magnetic resonance Elastography (DIME)

Primary: Acquisition & Reconstruction - Image Reconstruction: AI

Secondary: Acquisition & Reconstruction - AI methods

303-01-009 · AI Methods Beyond Reconstruction · Monday, 11 May, 8:20 AM–10:10 AM · Auditorium 1

Keywords: AI/ML Image Reconstruction Deep learning Magnetic Resonance Elastography MRE Inverse Problem

Accepted

Hassan Iftikhar, Rizwan Ahmad¹, Arunark Kolipaka^1,2,3

¹Department of Biomedical Engineering, The Ohio State University, Columbus, United States of America

²The Ohio State University, Columbus, United States of America

³Department of Radiology, The Ohio State University, Columbus, United States of America

Presenting Author: Samuel T Ting

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References

1. Muthupillai R, Lomas DJ, Rossman PJ, Greenleaf JF, Manduca A, Ehman RL. Magnetic Resonance Elastography by Direct Visualization of Propagating Acoustic Strain Waves. Science. 1995;269(5232):1854-1857. doi:10.1126/science.7569924 [doi]

2. Silva AM, Grimm RC, Glaser KJ, et al. Magnetic resonance elastography: evaluation of new inversion algorithm and quantitative analysis method. Abdom Imaging. 2015;40(4):810-817. doi:10.1007/s00261-015-0372-5 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/303-01-009