Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
662-04-008 ISMRM Abstract

Prospective Comparison of Conventional and Deep Learning-Reconstructed Thin-Slice 3D T1-weighted imaging of the Breast

Primary: Acquisition & Reconstruction - Image Reconstruction: AI
Secondary: Body - Breast
662-04-008 · Artificial Intelligence-Based Image Reconstruction in the Body · Thursday, 14 May, 2:35 PM–3:30 PM · Digital Posters Row C
Keywords: Breast cancer Deep learning SNR CNR Mass lesions
Accepted
Nan Zhang 1, Xuhao Song2,3, Caixia Fu4, Marcel Dominik Nickel5, Mengsu Zeng2
1Department of Radiology, Zhongshan Hospital, Shanghai, China
2Zhongshan Hospital, Shanghai, China
3Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
4MR Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
5Research & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany
Presenting Author: Nan Zhang

Synopsis

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References

1. Wei H, Yoon JH, Jeon SK, Choi JW, Lee J, Kim JH, Nickel MD, Song B, Duan T, Lee JM: Enhancing gadoxetic acid-enhanced liver MRI: a synergistic approach with deep learning CAIPIRINHA-VIBE and optimized fat suppression techniques. Eur Radiol 2024, 34(10):6712-6725.
2. Chaika M, Afat S, Wessling D, Afat C, Nickel D, Kannengiesser S, Herrmann J, Almansour H, Männlin S, Othman AE et al: Deep learning-based super-resolution gradient echo imaging of the pancreas: Improvement of image quality and reduction of acquisition time. Diagnostic and Interventional Imaging 2023, 104(2):53-59.
3. Wessling D, Gassenmaier S, Olthof SC, Benkert T, Weiland E, Afat S, Preibsch H: Novel deep-learning-based diffusion weighted imaging sequence in 1.5 T breast MRI. Eur J Radiol 2023, 166:110948

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/662-04-008