Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
304-02-010 ISMRM Abstract

Female pelvic floor diffusion tensor imaging enabled by multi-shot EPI and ADMM unrolled reconstruction

Primary: Acquisition & Reconstruction - Image Reconstruction: AI
Secondary: Diffusion - Diffusion Reconstruction
304-02-010 · Diffusion Acquisition and Reconstruction · Monday, 11 May, 8:20 AM–10:10 AM · Ballroom East
Keywords: Female pelvis Unrolled Networks and Reconstruction Self-supervised learning Pelvic Organ Prolapse Diffusion Tensor Imaging (DTI)
Accepted
Zhengguo Tan1, John DeLancey2, Yun Jiang1,3, Vikas Gulani 1
1Department of Radiology, University of Michigan, Ann Arbor, United States of America
2Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, United States of America
3Department of Biomedical Engineering, University of Michigan, Ann Arbor, United States of America
Presenting Author: Vikas Gulani

Synopsis

Motivation:
Goals:
Approach:
Results:
Full abstract & presentation

The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.

Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.

To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.

Log in

References

1. DeLancey J, Masteling M, Pipitone F, LaCross J, Mastrovito S, Ashton-Miller JA. Pelvic floor injury during vaginal birth is life-altering and preventable: what can we do about it? Am J Obstet Gynecol 2024;230:279-294. doi:10.1016/j.ajog.2023.11.1253 [doi]
2. Zifan A, Reisert M, Sinha S, et al. Connectivity of the superficial muscles of the human perineum: a diffusion tensor imaging-based global tractography study. Sci Rep 2018;8:17867. doi:10.1038/s41598-018-36099-4 [doi]
3. Tan Z, Liebig PA, Heidemann RM, Laun FB, Knoll F. Accelerated diffusion-weighted MRI at 7T: joint reconstruction for shift-encoded navigator-based interleaved EPI (JETS-NAViEPI). Imaging Neuroscience 2024;2:imag-2-00085. doi:10.1162/imag_a_00085 [doi]
4. Tan Z, Liebig PA, Hofmann A, Laun FB, Knoll F. High-resolution diffusion-weighted imaging with self-gated self-supervised unrolled reconstruction. Magn Reson Med (2025).
5. He K, Zhang X, Ren S, Sun J. Deep residual learning for image recognition. CVPR (2016). doi:10.1109/CVPR.2016.90 [doi]
6. aman B, Hosseini SAH, Moeller S, Ellermann J, Ugurbil K, Akcakaya M. Self-supervised learning of physics-guided reconstruction neural networks without fully sampled reference data. Magn Reson Med 2020;84:3172-3191. doi:10.1002/mrm.28378 [doi]
7. Yaman B, Hossein SAH, Akcakaya M. Zero-shot self-supervised learning for MRI reconstruction. ICLR (2022).
8. Pruessmann KP, Weiger M, Boernert P, Boesiger P. Advances in sensitivity encoding with arbitrary k-space trajectories. Magn Reson Med 2001;46:638-651. doi:10.1002/mrm.1241 [doi]
9. Chen NK, Guidon A, Chang HC, Song AW. A robust multi-shot scan strategy for high-resolution diffusion weighted MRI enabled by multiplexed sensitivity-encoding (MUSE). NeuroImage 2013;72:41-47. doi:10.1016/j.neuroimage.2013.01.038 [doi]
10. Cordero-Grande L, Christiaens D, Hutter J, Price AN, Hajnal JV. Complex diffusion-weighted image estimation via matrix recovery under general noise models. NeuroImage 2019;200:391-404. doi:10.1016.j.neuroimage.2019.06.039

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/304-02-010