Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
569-03-001 ISMRM Abstract

Deep Learning Reconstruction of Isotropic Structural MRI from Routine 2D Clinical Scans

Primary: Acquisition & Reconstruction - Image Reconstruction: AI
Secondary: Acquisition & Reconstruction - AI methods
569-03-001 · Super-Resolving MRI: Methods and Applications · Wednesday, 13 May, 1:40 PM–2:35 PM · Digital Posters Row J
Keywords: Structural T1 MRI Super-resolution reconstruction 3D super-resolution Structural and Functional MRI
Accepted
JiaChen Sun 1, Yayan Yin2, Boyan Xu3,4,5, Jie Lu1,2,6
1Xuanwu Hospital, Capital Medical University, Beijing, China
2Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
3MR Research China, GE Healthcare, Beijing, China
4MR Research, Beijing, China
5MR Research, GE Healthcare, Beijing, China
6xuanwu hospital of Capital Medical University, Beijing, China
Presenting Author: JiaChen Sun

Synopsis

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References

1. Song H, Mao X, Yu J, et al. I³Net: Inter-Intra-Slice Interpolation Network for Medical Slice Synthesis. IEEE Transactions on Medical Imaging, 2024, 43(9): 3306-3318. doi: 10.1109/TMI.2024.3394033. [doi]
2. Lee S, Chung H, Park M, et al. Improving 3D imaging with pre-trained perpendicular 2D diffusion models. Proceedings of the IEEE/CVF international conference on computer vision. 2023: 10710-10720. https://doi.org/10.1007/978-3-031-43999-5_42 [doi]
3. Liu G, Cao Z, Xu Q, et al. Recycling diagnostic MRI for empowering brain morphometric research–critical & practical assessment on learning-based image super-resolution. Neuroimage, 2021, 245: 118687. https://doi.org/10.1016/j.neuroimage.2021.118687 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/569-03-001