Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
667-04-004 ISMRM Abstract

Deep Learning Synthesis of Pseudo-CT from UTE-MRI for Temporal Bone Imaging

Primary: Acquisition & Reconstruction - Image Reconstruction: AI
Secondary: Musculoskeletal - Bone
667-04-004 · Novel Visualization and Assessment of Osseous Tissues · Thursday, 14 May, 2:35 PM–3:30 PM · Digital Posters Row H
Keywords: Deep learning Synthetic CT UTE-MRI
Accepted
Jinfu Niu1, Chaoqun Zhou2, Amaresha Konar Shridhar3, Isadora C Comens4, Elizabeth S Olson1, Jeffrey W Kysar2, Anil K Lalwani5, Jia Guo1,6
1Biomedical Engineering, Columbia University, New York, United States of America
2Mechanical Engineering, Columbia University, New York, United States of America
3Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, United States of America
4Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, United States of America
5Neurotology, Columbia University Vagelos College of Physicians and Surgeons, New York, United States of America
6Psychiatry, Columbia University, New York, United States of America
Presenting Author: Zongyu Li

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. Brenner DJ, Hall EJ. Computed tomography—an increasing source of radiation exposure. N Engl J Med. 2007;357(22):2277-2284.
2. Kaufman, A. C., et al. "Use of Ultra‐Short Echo Time MRI to Improve Temporal Bone Imaging." The Laryngoscope 134.11 (2024): 4691-4696.
3. Bahloul MA, Jabeen S, Benoumhani S, et al. Advancements in synthetic CT generation from MRI: A review of techniques, and trends in radiation therapy planning. J Appl Clin Med Phys. 2024;25(11):e14499.
4. Waring, Nicholas A., et al. "Sheep as a Large-Animal Model for Otology Research: Temporal Bone Extraction and Transmastoid Facial Recess Surgical Approach." Journal of the Association for Research in Otolaryngology 24.5 (2023): 487-497.
5. Yeiser, Aaron J., et al. "The UmboMic: A PVDF cantilever microphone." Journal of Micromechanics and Microengineering 34.8 (2024): 085010.
6. Waring, Nicholas A., et al. "Hampshire Sheep as a Large-Animal Model for Cochlear Implantation." Journal of the Association for Research in Otolaryngology 25.3 (2024): 277-284.
7. Barron JT. A general and adaptive robust loss function. Proc IEEE CVF Conf Comput Vis Pattern Recognit. 2019:4326-4334.
8. Liu D, et al. Enhancing transcranial focused ultrasound treatment planning with synthetic CT from ultra-short echo time (UTE) MRI: A multi-task deep learning approach. Proc IEEE Int Symp Biomed Imaging. 2024:1-5.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/667-04-004