  X-ray energy spectrum plays an essential role in imaging and related tasks.
Due to the high photon flux of clinical CT scanners, most of the spectrum
estimation methods are indirect and are usually suffered from various
limitations. The recently proposed indirect transmission measurement-based
method requires at least the segmentation of one material, which is
insufficient for CT images of highly noisy and with artifacts. To combat for
the bottleneck of spectrum estimation using segmented CT images, in this study,
we develop a segmentation-free indirect transmission measurement based energy
spectrum estimation method using dual-energy material decomposition. The
general principle of the method is to compare polychromatic forward projection
with raw projection to calibrate a set of unknown weights which are used to
express the unknown spectrum together with a set of model spectra. After
applying dual-energy material decomposition using high- and low-energy raw
projection data, polychromatic forward projection is conducted on
material-specific images. The unknown weights are then iteratively updated to
minimize the difference between the raw projection and estimated projection.
Both numerical simulations and experimental head phantom are used to evaluate
the proposed method. The results indicate that the method provides accurate
estimate of the spectrum and it may be attractive for dose calculations,
artifacts correction and other clinical applications.
