Development and Validation of a Multimodal 3D Brain Image Registration Algorithm for Alzheimer’s disease and Related Dementias
Motivation: Multimodal registration of brain images enables comprehensive integration of data between imaging modalities, enhancing our understanding of brain structure, function(s), and disease coping mechanisms. Goal(s): This study develops and validates a pipeline for multimodal image registration of MRI and PET data from ADRD subjects to a common atlas space. Approach: This framework utilizes a multi-stage approach, combining rigid and deformable registration, to align input images to the MNI152+ atlas for comparisons of brain anatomy and function. Results: This study generated a 3D registration framework for multimodal images, achieving a Structural Similarity Index Measure (SSIM) score of 0.9143±0.0288(n=337) across subjects with different ADRD stages. Impact: This study presents a 3D multimodal registration framework invariant to image contrast, spatial resolutions, and anatomical and functional variations; thus, enabling direct comparisons of brain anatomy and function(s) across subjects, while minimizing inter-subject variability, permitting quantitative multimodal analysis.
Authors
- Paul Salama (ORCID: https://orcid.org/0000-0002-7643-3879)
- Scott C. Persohn (ORCID: https://orcid.org/0000-0001-5047-8238)
- Paul R. Territo (ORCID: https://orcid.org/0000-0003-0460-332X)
- Juan Antonio Chong Chie
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/0526
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00