Fully Automated and Scalable Pipeline for Macaque Brain Registration Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.1101/2025.07.10.663842
With the rapid development of various whole-brain ex vivo imaging technologies, there is a growing need to develop cross-modal 3D image registration methods to integrate multimodal imaging datasets. While comprehensive cross-modality registration tools such as D-LMBmap and mBrainAligner have been successfully implemented for mouse brains, macaque whole-brain registration presents unique challenges. These include more pronounced non-uniform deformations in larger ex vivo specimens, greater modality-specific contrast differences relative to standard space, and increased inter-individual variability. To address these challenges, we developed Macaca-Star, which incorporates deep learning models and self-individual MRI to tackle cross-modal and ex vivo sample deformation challenges in macaque whole-brain registration. Macaca-Star provides fully automated alignment of fMOST and 2D fluorescent slice images to the NMT MRI standard space, allowing for comprehensive integration of anterograde axonal projections and retrograde-traced neuronal soma profiles.
Related Topics To Compare & Contrast
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2025.07.10.663842
- https://www.biorxiv.org/content/biorxiv/early/2025/07/16/2025.07.10.663842.full.pdf
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4412486858