360-02-007 ISMRM Abstract

Compressed SENSE AI enhanced mDixon-Quant MR Imaging in the liver Study

Primary: Body - Liver

Secondary: Acquisition & Reconstruction - Image Reconstruction: AI

360-02-007 · Machine Learning for Image Reconstruction · Monday, 11 May, 9:15 AM–10:10 AM · Digital Posters Row A

Keywords: Liver MRI MDixon-Quant Artificial Intelligence Compressed Sensing (AI-CS)

Accepted

Linzhe Li¹, Peng Wu ², Jun Peng²

¹Department of Medical Imaging, The Third Xiangya Hospital of Central South University, Changsha, China

²Philips Healthcare, Guangzhou, China

Presenting Author: Peng Wu

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References

1. CHALASANI N, YOUNOSSI Z, LAVINE J E, et al. The diagnosis and management of non-alcoholic fatty liver disease: practice guideline by the American Gastroenterological Association, American Association for the Study of Liver Diseases, and American College of Gastroenterology [J]. Gastroenterology, 2012, 142(7): 1592-609. PMID: 22656328 [pmid]

2. DAVIS T M E. Diabetes and metabolic dysfunction-associated fatty liver disease [J]. Metabolism, 2021, 123(154868). PMID: 34400217 [pmid]

3. JOHNSON P M, RECHT M P, KNOLL F. Improving the Speed of MRI with Artificial Intelligence [J]. Semin Musculoskelet Radiol, 2020, 24(1): 12-20. PMID: 31991448 [pmid]

4. AKçAKAYA M, MOELLER S, WEINGäRTNER S, et al. Scan-specific robust artificial-neural-networks for k-space interpolation (RAKI) reconstruction: Database-free deep learning for fast imaging [J]. Magn Reson Med, 2019, 81(1): 439-53. PMID: 30277269 [pmid]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/360-02-007