Signal to noise ratio of energy selective x-ray photon counting systems with pileup.

PURPOSE: To derive fundamental limits on the effect of pulse pileup and quantum noise in photon counting detectors on the signal to noise ratio (SNR) and noise variance of energy selective x-ray imaging systems.
METHODS: An idealized model of the response of counting detectors to pulse pileup is used. The model assumes a nonparalyzable response and delta function pulse shape. The model is used to derive analytical formulas for the noise and energy spectrum of the recorded photons with pulse pileup. These formulas are first verified with a Monte Carlo simulation. They are then used with a method introduced in a previous paper [R. E. Alvarez, "Near optimal energy selective x-ray imaging system performance with simple detectors," Med. Phys. 37, 822-841 (2010)] to compare the signal to noise ratio with pileup to the ideal SNR with perfect energy resolution. Detectors studied include photon counting detectors with pulse height analysis (PHA), detectors that simultaneously measure the number of photons and the integrated energy (NQ detector), and conventional energy integrating and photon counting detectors. The increase in the A-vector variance with dead time is also computed and compared to the Monte Carlo results. A formula for the covariance of the NQ detector is developed. The validity of the constant covariance approximation to the Cramèr-Rao lower bound (CRLB) for larger counts is tested.
RESULTS: The SNR becomes smaller than the conventional energy integrating detector (Q) SNR for 0.52, 0.65, and 0.78 expected number photons per dead time for counting (N), two, and four bin PHA detectors, respectively. The NQ detector SNR is always larger than the N and Q SNR but only marginally so for larger dead times. Its noise variance increases by a factor of approximately 3 and 5 for the A1 and A2 components as the dead time parameter increases from 0 to 0.8 photons per dead time. With four bin PHA data, the increase in variance is approximately 2 and 4 times. The constant covariance approximation to the CRLB is valid for larger counts such as those used in medical imaging.
CONCLUSIONS: The SNR decreases rapidly as dead time increases. This decrease places stringent limits on allowable dead times with the high count rates required for medical imaging systems. The probability distribution of the idealized data with pileup is shown to be accurately described as a multivariate normal for expected counts greater than those typically utilized in medical imaging systems. The constant covariance approximation to the CRLB is also shown to be valid in this case. A new formula for the covariance of the NQ detector with pileup is derived and validated.