Abstract #0936

AI-powered 0.3 mm Ultrahigh Resolution MR Brain Imaging

Ziwen Ke^1,2,3, Ziyang Xu^1,4, Huixiang Zhuang², Weijun Tang⁵, Yao Li^2,3, and Zhi-Pei Liang^1,4

¹Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ²School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, ³Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China, ⁴Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁵Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China

Synopsis

Keywords: Image Reconstruction, AI/ML Image Reconstruction

Motivation: Ultrahigh-resolution MRI is very challenging due to long scan time and signal-to-noise trade-offs. Machine learning provides new opportunities but, to our knowledge, has not been demonstrated due to limited training data available, huge computational demands, and potential morphological distortions.

Goal(s): To achieve generalizable ultrahigh-resolution MR brain imaging at 0.3 mm, using very limited data.

Approach: We proposed a diffusion bridge with model-based fake feature correction using 0.3 mm priors from one brain image and 1.0 mm priors from 10,000 brain images.

Results: Our approach successfully produced high-quality brain images at 0.3 mm, which were validated on both 13 public datasets and stroke patients.

Impact: Conventional MRI scans of the brain are typically done at 1 mm resolution. Ultrahigh-resolution MRI will open up many opportunities for research and clinical applications. The proposed approach may also be useful for solving other imaging and processing problems.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.