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BundleWarp: Enhancing white matter tractometry and morphometry with precise neuronal mapping using streamline-based nonlinear registration
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DOI：10.1016/j.media.2026.104114.png)
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Abstract
En 中文
• BundleWarp is introduced as a method for direct nonlinear registration of white matter bundles of streamlines. • The method supports partial to full deformation of a bundle by adjusting a single parameter, λ . • Bundle shape analysis is performed using the deformation field generated by BundleWarp. • Tractometry robustness and reliability are enhanced through accurate tract alignment across diverse populations. • BundleWarp is evaluated and compared with existing streamline-based and image-based registration methods. • Extensive experiments demonstrate the consistency, reliability, and impact of BundleWarp on tractometric studies. • Results are presented using diverse datasets, including participants with Parkinson’s disease, Mild Cognitive Impairment (MCI), and dementia. Early-stage Alzheimer’s biomarkers, such as amyloid-beta plaques and tau neurofibrillary tangles, are incorporated into the analyses.
Keywords:
BundleWarp
white matter bundles
streamline-based registration
tractometry
morphometry
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