Abstract #1116

Towards Metadata-customized Brain MR image Synthesis for Disease Diagnosis

Yulin Wang¹, Honglin Xiong¹, Kaicong Sun¹, Shuwei Bai^1,2, Zhongxiang Ding³, Qian Wang^1,2, Qian Liu^4,5, and Dinggang Shen^1,2,6

¹School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, Shanghaitech University, Shanghai, China, ²Shanghai Clinical Research and Trial Center, Shanghai, China, ³Department of Radiology, Affiliated Hangzhou First People's Hospital, Xihu University School of Medicine, Hangzhou, China, ⁴School of Biomedical Engineering and State Key Laboratory of Digital Medical Engineering, Hainan University, Haikou, China, ⁵Key Laboratory of Biomedical Engineering of Hainan Province, One Health Institute, Hainan University, Haikou, China, ⁶Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China

Synopsis

Keywords: Synthetic MR, Multi-Contrast, Brain

Motivation: Multi-modal MR images are vital to various disease diagnosis. Lengthy acquisition time limits its clinical applications. MRI synthesis can be an alternative to mitigating this issue.

Goal(s): We aim to develop a general multi-modal MRI synthesis model capable of generating metadata-specified brain MR images from acquired scans.

Approach: We compile a dataset of 31,407 3D brain MR scans. An MRI-dedicated text encoder is pre-trained to extract features from textual metadata, empowering the MR image synthesis model to precisely yield metadata-specified images.

Results: Our generative foundation model provides reliable MRI sequences according to specified scanning parameters, and demonstrates superior generalizability across multi-center data.

Impact: Our general multimodal MRI synthesis foundation model is capable of quickly and cost-effectively providing metadata-tailored multiple MR sequences, enabling clinicians and researchers to customize the desired MR images using this convenient AI technology, thereby enhancing diagnostic precision and efficiency.

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.