552-02-004 / 552-02-004 ISMRM Abstract

Fast Whole-Brain Multi-Parameter Mapping with Scan-Specific, Unsupervised Hybrid-Regularized Networks

Primary: Acquisition & Reconstruction - Quantitative Imaging: relaxometry, multi-parametric, MR Fingerprinting, and synthetic MRI

Secondary: Acquisition & Reconstruction - AI methods

552-02-004 · Quantitative Imaging: Relaxometry, Multiparametric, MR Fingerprinting, and Synthetic MRI · Wednesday, 13 May, 1:40 PM–3:16 PM · Power Pitch Theatre 2

Keywords: Quantitative MRI Unsupervised learning Whole-brain Scan-Specific Networks

Accepted

Amir Heydari¹, Tae Hyung Kim², Yuting Chen^3,4,5, Yohan Jun^5,6, Abbas Ahmadi¹, Berkin Bilgic ^5,6

¹Industrial Engineering and Managenent Systems, Amirkabir University of Technology, Tehran, Iran (Islamic Republic of)

²Department of Computer Engineering, Hongik University, Seoul, Korea, Republic of

³State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, China

⁴Massachusetts General Hospital, Boston, United States of America

⁵Radiology, Harvard Medical School, Boston, United States of America

⁶Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, United States of America

Presenting Author: Berkin Bilgic

Synopsis

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References

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Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/552-02-004