[2603.04638] Spinverse: Differentiable Physics for Permeability-Aware Microstructure Reconstruction from Diffusion MRI

Computer Science > Computer Vision and Pattern Recognition arXiv:2603.04638 (cs) [Submitted on 4 Mar 2026] 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 View a PDF of the paper titled Spinverse: Differentiable Physics for Permeability-Aware Microstructure Reconstruction from Diffusion MRI, by Prathamesh Pradeep Khole and 7 other authors View PDF HTML (experimental) 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. ...