CT scans without X-rays: parallel-beam imaging from nonlinear current flows

TL;DR

This paper reveals a surprising connection between electrical impedance tomography and X-ray CT, enabling the creation of CT-like images from electrical data through a novel method called virtual hybrid parallel-beam tomography.

Contribution

It introduces VHPT, a new imaging modality that separates ill-posedness and nonlinearity in EIT, allowing CT-like imaging from electrical measurements.

Findings

VHPT produces CT-like images from electrical data.

EIT data contains hidden linear geometry similar to CT.

Proof-of-concept images of real objects demonstrate feasibility.

Abstract

Parallel-beam X-ray computed tomography (CT) and electrical impedance tomography (EIT) are two imaging modalities which stem from completely different underlying physics, and for decades have been thought to have little in common either practically or mathematically. CT is only mildly ill-posed and uses straight X-rays as measurement energy, which admits simple linear mathematics. However, CT relies on exposing targets to ionizing radiation and requires cumbersome setups with expensive equipment. In contrast, EIT uses harmless electrical currents as measurement energy and can be implemented using simple low-cost portable setups. But EIT is burdened by nonlinearity stemming from the curved paths of electrical currents, as well as extreme ill-posedness which causes characteristic low spatial resolution. In practical EIT reconstruction methods, nonlinearity and ill-posedness have been considered intertwined in a complicated fashion. In this work we demonstrate a surprising connection between CT and EIT which partly unravels the main problems of EIT and leads directly to a proposed imaging modality which we call virtual hybrid parallel-beam tomography (VHPT). We show that hidden deep within EIT data is information which possesses the same linear geometry as parallel-beam CT data. This admits a fundamental restructuring of EIT, separating ill-posedness and nonlinearity into simple modular sub-problems, and yields ''virtual radiographs'' and CT-like images which reveal previously concealed information. Furthermore, as proof of concept we present VHPT images of real-world objects.