Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
568-05-006 ISMRM Abstract

Breaking the Speed-Quality Trade-off in Prostate T2-Weighted Imaging: A Deep Learning Reconstruction Approach

Primary: Acquisition & Reconstruction
Secondary: Acquisition & Reconstruction
568-05-006 · Image Reconstruction I · Wednesday, 13 May, 4:00 PM–4:55 PM · Digital Posters Row I
Keywords: Prostate Deep learning reconstruction Magnetic Resonance Imaging (MRI) T2-weighted imaging
Accepted
Huili Wang 1, Caohui Duan1, yumeng li2, song Wang2, Xiangbing Bian1, Lizhi Xie3, Xin Lou1
1Department of Radiology, The First Medical Center, Chinese PLA General Hospital, Beijing, China
2The First Medical Center, Chinese PLA General Hospital, Beijing, China
3MRI Research, GE Healthcare, Beijing, China
Presenting Author: Huili Wang

Synopsis

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References

1. TRECARTEN S, SUNNAPWAR A G, CLARKE G D, et al. Prostate MRI for the detection of clinically significant prostate cancer: Update and future directions [J]. Adv Cancer Res, 2024, 161: 71-118.doi:10.1016/bs.acr.2024.04.002. [doi]
2. TANG H, HONG M, YU L, et al. Deep learning reconstruction for lumbar spine MRI acceleration: a prospective study [J]. Eur Radiol Exp, 2024, 8(1): 67.doi:10.1186/s41747-024-00470-0. [doi]
3. KANIEWSKA M, DEININGER-CZERMAK E, GETZMANN J M, et al. Application of deep learning-based image reconstruction in MR imaging of the shoulder joint to improve image quality and reduce scan time [J]. Eur Radiol, 2023, 33(3): 1513-25.doi:10.1007/s00330-022-09151-1. [doi]
4. HOKAMURA M, NAKAURA T, YOSHIDA N, et al. Super-resolution deep learning reconstruction approach for enhanced visualization in lumbar spine MR bone imaging [J]. Eur J Radiol, 2024, 178: 111587.doi:10.1016/j.ejrad.2024.111587. [doi]
5. KIDOH M, SHINODA K, KITAJIMA M, et al. Deep Learning Based Noise Reduction for Brain MR Imaging: Tests on Phantoms and Healthy Volunteers [J]. Magn Reson Med Sci, 2020, 19(3): 195-206.doi:10.2463/mrms.mp.2019-0018. [doi]

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http://echo.ismrm.org/p/ISMRM2026/568-05-006