360-02-011 ISMRM Abstract

Application of AI-assisted compressed sensing combined with deep learning-based reconstruction in sacroiliac joint MRI

Primary: Acquisition & Reconstruction - Image Reconstruction: AI

Secondary: Musculoskeletal - Other Musculoskeletal

360-02-011 · Machine Learning for Image Reconstruction · Monday, 11 May, 9:15 AM–10:10 AM · Digital Posters Row A

Keywords: Magnetic Resonance Imaging (MRI) AI-assisted compressed sensing Sacroiliac joint Deep learning-based reconstruction

Accepted

Kangyu Zhang ¹, Zhenghua He¹, Jian Wang¹, Guobin Hong¹, Shilong Lu¹, Jing Yang²

¹Zhujiang Hospital, Southern Medical University, Guangzhou, China

²Collaborative Innovation Department, United Imaging Healthcare, Shanghai, China

Presenting Author: Kangyu Zhang

Synopsis

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References

1. Vereecke E, Diekhoff T, Eshed I, et al. ESR Essentials: Imaging of sacroiliitis-practice recommendations by ESSR. Eur Radiol. 2024 Sep;34(9):5773-5782.

2. Zhao Q, Xu J, Yang YX, et al. Yuan H. AI-assisted accelerated MRI of the ankle: clinical practice assessment. Eur Radiol Exp. 2023 Oct 20;7(1):62.

3. Ni M, He M, Yang Y, et al. Application research of AI-assisted compressed sensing technology in MRI scanning of the knee joint: 3D-MRI perspective. Eur Radiol. 2024 May;34(5):3046-3058.

4. Wang Q, Zhao W, Xing X, et al. Feasibility of AI-assisted compressed sensing protocols in knee MR imaging: a prospective multi-reader study. Eur Radiol. 2023 Dec;33(12):8585-8596.

5. Wang S, Cao G, Wang Y, et al. Review and Prospect: Artificial Intelligence in Advanced Medical Imaging. Front Radiol. 2021 Dec 13;1:781868.

6. Wen Y, Ma H, Xiang S, et al. Accelerating brain T2-weighted imaging using artificial intelligence-assisted compressed sensing combined with deep learning-based reconstruction: a feasibility study at 5.0T MRI. BMC Med Imaging. 2025 Jul 1;25(1):224.

7. Iuga AI, Abdullayev N, Weiss K, et al. Accelerated MRI of the knee. Quality and efficiency of compressed sensing. Eur J Radiol. 2020 Nov;132:109273.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/360-02-011