Meeting Banner
Abstract #3817

A Registration-Based Framework for Generating Aligned CT Images from Misaligned CBCT-CT Pairs

Abdalla Shazly1, Daniel Kim2, Abdulkhalek Al-Fakih1, Abbas Mohamed Rezk1, Kanghyun Ryu3, and Mohammed A. Al-masni1
1Department of Artificial Intelligence and Data Science, College of AI Convergence, Sejong University, Seoul, Korea, Republic of, 2Department of Electrical and Electronic Engineering, College of Engineering, Yonsei University, Seoul, Korea, Republic of, 3Artificial Intelligence and Robotics Institute, Korea Institute of Science and Technology, Seoul, Korea, Republic of

Synopsis

Keywords: Analysis/Processing, AI/ML Image Reconstruction, Multi-modal images, Registration, Generation, Transformer, Cross-attention, image translation.

Motivation: As Cone Beam Computed Tomography (CBCT) becomes more prevalent in clinical applications, accurately registering Computed Tomography (CT) to CBCT images is critical, yet challenging due to CBCT’s lower image quality and complex anatomical distortions.

Goal(s): Generate aligned CT images via spatial transformations and guided cross attention within a custom module.

Approach: Registration by Generation (RbG), a self-supervised framework that uses misaligned CT images as a reference guiding Deformation-Aware Cross Attention (DACA), aligning CT to CBCT with high fidelity and structural consistency.

Results: The proposed RbG method demonstrates superior performance compared to traditional and deep learning registration and image translation methodologies across all metrics.

Impact: This methodology eliminates the need for perfectly aligned inputs, which are often unavailable in practice. By using the misaligned CT image as a proxy label, the proposed self-supervised approach leverages CBCT information to enhance the high-quality aligned CT (aCT) format.

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