  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.
