Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
565-06-001 ISMRM Abstract

Clinical Evaluation of Deep Learning Accelerated Lumbar T2-Weighted and Fat-Suppressed MRI Sequences

Accepted
Ran Lv , Nan Chen1, Yijiang Huang2, Hongtao Hou, Marcel D Nickel3, Yunzhu Wu4, Guoqun Mao2, Fuquan Wei2,5
1Zhejiang Chinese Medicine University, Hangzhou, China
2Department of Radiology, Tongde Hospital of Zhejiang Province, Hangzhou, China
3Research & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany
4MR Research Collaboration Team, Shanghai, China
5Tongde Hospital of Zhejiang Province, Hangzhou, China
Presenting Author: Ran Lv

Synopsis

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References

1. [1] BEATTIE P F, MEYERS S P. Magnetic resonance imaging in low back pain: general principles and clinical issues[J]. Physical Therapy, 1998, 78(7): 738–753. DOI:10.1093/ptj/78.7.738. [doi]
2. [2] TABER K H, HERRICK R C, WEATHERS S W, et al. Pitfalls and artifacts encountered in clinical MR imaging of the spine[J]. Radiographics, 1998, 18(6): 1499–1521. DOI:10.1148/radiographics.18.6.9821197. [doi]
3. [3] ZENG G, GUO Y, ZHAN J, et al. A review on deep learning MRI reconstruction without fully sampled k-space[J]. BMC Med. Imaging, 2021, 21(1): 195. DOI:10.1186/s12880-021-00727-9. [doi]
4. [4] ZUNAIR H, BEN HAMZA A. Sharp U-Net: Depthwise convolutional network for biomedical image segmentation[J]. Comput. Biol. Med., 2021, 136: 104699. DOI:10.1016/j.compbiomed.2021.104699. [doi]
5. [5] MUCKLEY M J, RIEMENSCHNEIDER B, RADMANESH A, et al. Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction[J]. IEEE Trans. Med. Imag., 2021, 40(9): 2306–2317. DOI:10.1109/TMI.2021.3075856. [doi]
6. [6] SOO T H, SUPPIAH S, THAREK A, et al. Sociodemographic influences on lumbar disc degeneration severity and the diagnostic potential of disc‑CSF signal ratio: insights from a south east Asia population study[J]. J. Belg. Soc. Radiol., 2025, 109(1): 10. DOI:10.5334/jbsr.3801. [doi]
7. [7] BRANDÃO S, SEIXAS D, AYRES-BASTO M, et al. Comparing T1-weighted and T2-weighted three-point dixon technique with conventional T1-weighted fat-saturation and short-tau inversion recovery (STIR) techniques for the study of the lumbar spine in a short-bore MRI machine[J]. Clin. Radiol., 2013, 68(11): e617–e623. DOI:10.1016/j.crad.2013.06.004. [doi]

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