Spinverse: Differentiable Physics for Permeability-Aware Microstructure Reconstruction from Diffusion MRI

• URL: http://arxiv.org/abs/2603.04638v1
• Date: Wed, 04 Mar 2026 21:57:40 GMT
• Title: Spinverse: Differentiable Physics for Permeability-Aware Microstructure Reconstruction from Diffusion MRI
• Authors: Prathamesh Pradeep Khole, Mario M. Brenes, Zahra Kais Petiwala, Ehsan Mirafzali, Utkarsh Gupta, Jing-Rebecca Li, Andrada Ianus, Razvan Marinescu,
• Abstract summary: We present Spinverse, a permeability-aware reconstruction method that inverts dMRI measurements.<n>Spinverse represents tissue on a fixed tetrahedral grid and treats each interior face permeability as a learnable parameter.<n>It reconstructs diverse geometries and demonstrates that sequence scheduling and regularization are critical to avoid outline-only solutions.
• Score: 1.6863755729554886
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Diffusion MRI (dMRI) is sensitive to microstructural barriers, yet most existing methods either assume impermeable boundaries or estimate voxel-level parameters without recovering explicit interfaces. We present Spinverse, a permeability-aware reconstruction method that inverts dMRI measurements through a fully differentiable Bloch-Torrey simulator. Spinverse represents tissue on a fixed tetrahedral grid and treats each interior face permeability as a learnable parameter; low-permeability faces act as diffusion barriers, so microstructural boundaries whose topology is not fixed a priori (up to the resolution of the ambient mesh) emerge without changing mesh connectivity or vertex positions. Given a target signal, we optimize face permeabilities by backpropagating a signal-matching loss through the PDE forward model, and recover an interface by thresholding the learned permeability field. To mitigate the ill-posedness of permeability inversion, we use mesh-based geometric priors; to avoid local minima, we use a staged multi-sequence optimization curriculum. Across a collection of synthetic voxel meshes, Spinverse reconstructs diverse geometries and demonstrates that sequence scheduling and regularization are critical to avoid outline-only solutions while improving both boundary accuracy and structural validity.

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