Electrical and Bioimpedance Tomography

Últimos artículos

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

  Djahid Abdelmoumene, Ishak Ayad, Ma\"i K. Nguyen, Christian Daveau · 1 de julio de 2026

  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-…

• An Electric Potential-Augmented Benchmark Dataset for Physics-Guided Image Reconstruction of Electrical Capacitance Tomography

  Xinqi Zhang, Qiming Ma, Lihui Peng · 11 de junio de 2026

  While deep learning has significantly advanced image reconstruction of Electrical Capacitance Tomography (ECT), most data-driven methods map directly between capacitance and permittivity distribution, treating the sensor as a black box. This overlooks the electric potential field -- the fundamental …

• Bound-Constrained Sparse Representation for Electrical Impedance Tomography

  Chun Zhang, Dong Liu · 28 de mayo de 2026

  This study proposes a bound-constrained sparse representation (BC-SR) framework for electrical impedance tomography (EIT), aimed at improving conductivity estimation without explicit regularization. BC-SR adopts a representation-driven strategy, generating conductivity from low-dimensional latent va…

• Diffusion Graph Posterior Sampling for Nonlinear Inverse Problems with Application to Electrical Impedance Tomography

  Giovanni S. Alberti, Damiana Lazzaro, Serena Morigi, Matteo Santacesaria, Shibo Wang · 20 de mayo de 2026

  Deep generative models have emerged as state-of-the-art for solving inverse problems, but applying them to inverse problems for PDEs, like electrical impedance tomography (EIT) remains challenging. Because physical domains are naturally discretized as unstructured meshes rather than regular grids, s…

• A DeepONet for inverting the Neumann-to-Dirichlet Operator in Electrical Impedance Tomography: An approximation theoretic perspective and numerical results

  Anuj Abhishek, Thilo Strauss · 15 de abril de 2026

  In this work, we consider the non-invasive medical imaging modality of Electrical Impedance Tomography (EIT), where the goal is to recover the conductivity in a medium from boundary current-to-voltage measurements, i.e., the Neumann-to-Dirichlet (N--t--D) operator. We formulate this inverse problem …

• A Physics-Embedded Dual-Learning Imaging Framework for Electrical Impedance Tomography

  Xuanxuan Yang, Yangming Zhang, Haofeng Chen, Gang Ma, Xiaojie Wang · 16 de diciembre de 2025

  Electrical Impedance Tomography (EIT) is a promising noninvasive imaging technique that reconstructs the spatial conductivity distribution from boundary voltage measurements. However, it poses a highly nonlinear and ill-posed inverse problem. Traditional regularization-based methods are sensitive to…