BREIT: A Framework for Brain Stroke Reconstruction using Multi-Frequency 3D EIT

• URL: http://arxiv.org/abs/2606.28787v2
• Date: Tue, 30 Jun 2026 09:17:24 GMT
• Title: BREIT: A Framework for Brain Stroke Reconstruction using Multi-Frequency 3D EIT
• Abstract summary: Multi-Frequency Electrical Impedance Tomography (MF-EIT) is a non-invasive, low-cost modality that reconstructs electrical property distributions from boundary voltages.<n>For stroke imaging, progress in 3D deep-learning reconstruction is limited by the lack of large-scale datasets with paired ground-truth (GT) volumes.<n>We introduce B, a modular framework for 3D MF-EIT stroke reconstruction providing: (i) a Fourier-to-EIT pipeline that converts CT/MRI into frequency-dependent GT admittivity volumes; (ii) a Python 3D Complete Electrode Model (CEM) forward
• Score: 2.3332469289621787
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Multi-Frequency Electrical Impedance Tomography (MF-EIT) is a non-invasive, low-cost modality that reconstructs electrical property distributions from boundary voltages. For stroke imaging, progress in 3D deep-learning reconstruction is limited by the lack of large-scale datasets with paired ground-truth (GT) volumes and by non-standardized pipelines for data generation, simulation, and evaluation. We introduce BREIT, a modular framework for 3D MF-EIT stroke reconstruction providing: (i) a neuroimaging-to-EIT pipeline that converts CT/MRI into frequency-dependent GT admittivity volumes; (ii) a self-contained Python 3D Complete Electrode Model (CEM) forward solver for simulating MF-EIT voltages; and (iii) a 3D D-bar implementation supporting non-uniform electrode layouts. Building on BREIT, we propose dFNO-bar, which integrates Fourier Neural Operators into D-bar by learning a mapping from scattering data $t(ξ)$ to conductivity $σ(x){=}\Re\{γ\}$. We evaluate dFNO-bar against D-bar, Deep D-bar, and Gauss--Newton reconstructions on UCLH-matched synthetic data, and observe higher brain SSIM with comparable CC across noise settings.

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