Deep Learning Approaches for Computational Inverse Problem in Electrical Impedance Tomography.

Abstract

We provide an overview of machine learning approaches for solving the computational image reconstruction problems in electrical impedance tomography (EIT). We will present how deep learning approaches compare to deterministic regularization such as sparsity and smoothness for EIT using simulated data.

Publication
In Spring Southeastern Virtual Sectional Meeting)
Date