Segmentation-Free X-ray Energy Spectrum Estimation for Computed Tomography Using Dual-Energy Material Decomposition

TL;DR

This paper introduces a novel segmentation-free method for estimating X-ray energy spectra in CT using dual-energy material decomposition, which is robust, accurate, and does not require physical phantoms.

Contribution

It proposes a new indirect spectrum estimation technique based on minimizing quadratic error with dual-energy data, eliminating the need for segmentation and physical phantoms.

Findings

Accurately estimates X-ray spectra matching reference spectra.

Robust across numerical, phantom, and patient data.

Simplifies workflow for spectrum estimation in CT.

Abstract

X-ray energy spectrum plays an essential role in computed tomography (CT) imaging and related tasks. Due to the high photon flux of clinical CT scanners, most of spectrum estimation methods are indirect and usually suffered from various limitations. In this study, we aim to provide a segmentation-free indirect transmission measurement-based energy spectrum estimation method using dual-energy material decomposition. The general principle of the method is to minimize the quadratic error between the polychromatic forward projection and the raw projection to calibrate a set of unknown weights which are used to express the unknown spectrum together with a set of model spectra. The polychromatic forward projection is performed using material-specific images which are obtained using dual-energy material decomposition. The algorithm has been evaluated using numerical simulations, experimental phantom data as well as realistic patient data. The results show the estimated spectrum matches the reference spectrum quite well and the method is robust. Extensive studies suggest the method provides accurate estimate of the CT spectrum without dedicated physical phantom and prolonged work flow. This paper may be attractive for CT dose calculations, artifacts reduction, polychromatic image reconstruction and other spectrum-involved CT applications.