Spectral photon counting for panoramic dental imaging.

Panoramic x-ray imaging is a versatile, low-dose imaging tool, which is routinely used for dental applications. In this work, we explore a further improvement of the concept by introducing recently developed spectral photon-counting detector technology into a conventional panoramic imaging unit. In addition we adapt spectral material decomposition algorithms to panoramic imaging needs. Finally, we provide first experimental results, demonstrating decomposition of an anthropomorphic head phantom into soft tissue and dentin basis material panoramic images, while keeping the noise level acceptable using regularization approaches. The obtained results reveal a potential benefit of spectral photon-counting technology also for dental imaging applications.

Basis material decomposition in spectral CT using a semi-empirical, polychromatic adaption of the Beer-Lambert model.

Following the development of energy-sensitive photon-counting detectors using high-Z sensor materials, application of spectral x-ray imaging methods to clinical practice comes into reach. However, these detectors require extensive calibration efforts in order to perform spectral imaging tasks like basis material decomposition. In this paper, we report a novel approach to basis material decomposition that utilizes a semi-empirical estimator for the number of photons registered in distinct energy bins in the presence of beam-hardening effects which can be termed as a polychromatic Beer-Lambert model. A maximum-likelihood estimator is applied to the model in order to obtain estimates of the underlying sample composition. Using a Monte-Carlo simulation of a typical clinical CT acquisition, the performance of the proposed estimator was evaluated. The estimator is shown to be unbiased and efficient according to the Cramér-Rao lower bound. In particular, the estimator is capable of operating with a minimum number of calibration measurements. Good results were obtained after calibration using less than 10 samples of known composition in a two-material attenuation basis. This opens up the possibility for fast re-calibration in the clinical routine which is considered an advantage of the proposed method over other implementations reported in the literature.