Meeting Banner
Abstract #4200

Enhancing OGSE Image Quality Using Deep Learning and Distortion Correction for the Estimation of Smaller Cellular Structures at 7T

Tianxiong Wu1,2, Tao Zhang1,2, Huilou Liang3, Yuhui Xiong3, Ying Song4, Jiayu Sun5, Min Wu2, and Haoyang Xing1,2
1College of Physics, Sichuan University, Chengdu, China, 2Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China, 3GE HealthCare MR Research, Beijing, China, 4Department of Radiotherapy, Cancer Center, West China Hospital of Sichuan University, Chengdu, China, 5Department of Radiology, West China Hospital of Sichuan University, Chengdu, China

Synopsis

Keywords: Diffusion Reconstruction, Diffusion Denoising

Motivation: High-resolution imaging of small cellular structures remains a challenge in clinical MRI due to limitations in existing diffusion sequences and hardware.

Goal(s): The study aims to improve image quality using deep learning (DL) and distortion correction (DC) techniques, applying them to MR cell size imaging at 7T.

Approach: The IMPULSED model was applied using PGSE and OGSE sequences at 7T, incorporating DC and DL methods for image enhancement, and the clinical feasibility was assessed.

Results: The improved images demonstrated clearer structural details, with DL significantly reducing noise and DC effectively correcting distortion, offering potential for finer microstructural analysis.

Impact: This study enables higher-resolution MR imaging of small cellular structures at 7T using deep learning (DL) and distortion correction (DC), potentially enhancing diagnostic capabilities in neurology and oncology, and encouraging further exploration of microstructural analysis in clinical practice.

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.

Keywords