Meeting Banner
Abstract #3235

Diffusion-guided MR Brain Tumor Segmentation with Missing Modalities

Yajing Zhang1, Yanxin Huang2, and Jin Qi2
1GE Healthcare, Beijing, China, 2University of Electronic Science and Technology of China, Chengdu, China

Synopsis

Keywords: Analysis/Processing, Segmentation

Motivation: Accurate brain tumor segmentation is crucial for effective diagnosis and treatment but is often complicated by missing MRI modalities in clinical practice。

Goal(s): This study introduces a diffusion-guided multi-modal segmentation framework designed to handle missing MRI modalities, a frequent challenge in clinical tumor segmentation.

Approach: By combining a CNN-based model and a diffusion-based model, the framework adapts to incomplete data, providing robust and accurate segmentation results.

Results: Testing on the BRATS2023GLIT dataset shows that this approach outperforms conventional methods, demonstrating improved segmentation.

Impact: This approach enhances brain tumor segmentation accuracy and consistency, even with missing MRI modalities, thereby improving diagnostic precision and supporting clinical decision-making.

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