A radiation detector includes a charge generation part configured to generate charge corresponding to energy of an incident radiation, a preamplification part configured to output an analog signal corresponding to the charge, a signal conversion part configured to receive the analog signal and output a digital signal being the analog signal that has been discretized, an energy discrimination part configured to compare the digital signal to a threshold value and output components of the digital signal exceeding the threshold value, and an energy integration part configured to obtain an energy integrated value defined as a summation of the components exceeding the threshold value obtained each time the radiation enters.

A nuclear reaction detection device has a detection circuit section (123) that detects an SEF that is an error causing a logical abnormality in an FPGA (100), and a CRAM monitoring circuit 102 and a number-of-errors determination unit 130 that detect a bit error occurring in the FPGA (100) and further determine whether the bit error is an SBU that is an error of one bit or an MBU that is an error of multiple bits. The nuclear reaction detection device further includes an SBU cross-section calculation section (231) that detects the energy of a particle that has caused an SEF, and calculates an SBU cross-section based on the energy and a total number of SBUs that have occurred in the FPGA (100), and an MBU cross-section calculation section (232) that calculates an MBU cross-section based on the energy and a total number of MBUs that have occurred in the FPGA (100).

A nuclear reaction detection device has a detection circuit section (123) that detects an SEF that is an error causing a logical abnormality in an FPGA (100), and a CRAM monitoring circuit 102 and a number-of-errors determination unit 130 that detect a bit error occurring in the FPGA (100) and further determine whether the bit error is an SBU that is an error of one bit or an MBU that is an error of multiple bits. The nuclear reaction detection device further includes an SBU cross-section calculation section (231) that detects the energy of a particle that has caused an SEF, and calculates an SBU cross-section based on the energy and a total number of SBUs that have occurred in the FPGA (100), and an MBU cross-section calculation section (232) that calculates an MBU cross-section based on the energy and a total number of MBUs that have occurred in the FPGA (100).

An X-ray detector is disclosed, including a detection unit to generate a detection signal for incident X-ray radiation; a signal analysis module to determine a set of count rates for incident X-ray radiation based upon the detection signal and signal analysis parameters for X-ray radiation; and a switchover control unit for switching between first signal analysis parameters and second signal analysis parameters. When an amount of X-ray radiation is incident on the detection module, a first set of count rates is generated for a first time interval based upon first signal analysis parameters and a second set of count rates is generated for a second time interval based upon second signal analysis parameters, different from the first signal analysis parameters. An X-ray imaging system including the detector; a method for determining count rates for X-ray radiation; and a method for calibrating signal analysis parameters are also disclosed.

An X-ray detector is disclosed, including a detection unit to generate a detection signal for incident X-ray radiation; a signal analysis module to determine a set of count rates for incident X-ray radiation based upon the detection signal and signal analysis parameters for X-ray radiation; and a switchover control unit for switching between first signal analysis parameters and second signal analysis parameters. When an amount of X-ray radiation is incident on the detection module, a first set of count rates is generated for a first time interval based upon first signal analysis parameters and a second set of count rates is generated for a second time interval based upon second signal analysis parameters, different from the first signal analysis parameters. An X-ray imaging system including the detector; a method for determining count rates for X-ray radiation; and a method for calibrating signal analysis parameters are also disclosed.

A neural network based corrector for photon counting detectors is described. A method for photon count correction includes receiving, by a trained artificial neural network (ANN), a detected photon count from a photon counting detector. The detected photon count corresponds to an attenuated energy spectrum. The attenuated energy spectrum is related to characteristics of an imaging object and is based, at least in part, on an incident energy spectrum. The method further includes correcting, by the trained ANN, the detected photon count to produce a corrected photon count. The method may include reconstructing, by image reconstruction circuitry, an image based, at least in part, on the corrected photon count.

A neural network based corrector for photon counting detectors is described. A method for photon count correction includes receiving, by a trained artificial neural network (ANN), a detected photon count from a photon counting detector. The detected photon count corresponds to an attenuated energy spectrum. The attenuated energy spectrum is related to characteristics of an imaging object and is based, at least in part, on an incident energy spectrum. The method further includes correcting, by the trained ANN, the detected photon count to produce a corrected photon count. The method may include reconstructing, by image reconstruction circuitry, an image based, at least in part, on the corrected photon count.

One or more techniques and/or systems are described for addressing (e.g., during calibration) pixel-by-pixel variations in an image modality that utilizes photon counting techniques, such as by adjusting a number of photons detected by certain pixels (e.g., redistributing or reallocating detected photons among pixels). Such variations may cause an effective area of one or more pixels of a detector array to be larger than the effective area of other pixels, resulting in more photons being counted by some pixels than others, which can degrade resulting images. Accordingly, photons are redistributed as provided herein so that, when exposed to substantially uniform radiation, photon counts of neighboring pixels are substantially equal, statistical noise among neighboring pixels is substantially equal, and a signal-to-noise ratio among neighboring pixels is substantially equal. By redistributing photons as described herein, a spatial uniformity and/or a modulated transfer function (MTF) associated with a detector array may be improved.

One or more techniques and/or systems are described for addressing (e.g., during calibration) pixel-by-pixel variations in an image modality that utilizes photon counting techniques, such as by adjusting a number of photons detected by certain pixels (e.g., redistributing or reallocating detected photons among pixels). Such variations may cause an effective area of one or more pixels of a detector array to be larger than the effective area of other pixels, resulting in more photons being counted by some pixels than others, which can degrade resulting images. Accordingly, photons are redistributed as provided herein so that, when exposed to substantially uniform radiation, photon counts of neighboring pixels are substantially equal, statistical noise among neighboring pixels is substantially equal, and a signal-to-noise ratio among neighboring pixels is substantially equal. By redistributing photons as described herein, a spatial uniformity and/or a modulated transfer function (MTF) associated with a detector array may be improved.

A method for digitalizing a scintillation pulse may include: S1, acquiring a pulse database outputted by a detector irradiated by rays of different energy; S2, sampling and 5 quantizing each of pulses in the pulse database obtained in S1 to acquire complete energy information comprised in the pulse; S3, undersampling and quantizing each of the pulses in the pulse database obtained in step S1, and estimating or fitting energy information by using pulse prior information; S4, with the energy information obtained in S2 as a standard, determining a mapping relationship between 10 the energy information obtained by a prior information-based undersampling pulse energy acquisition method and the energy information obtained by the method of S2; and S5 correcting the energy information obtained by the prior information-based undersampling pulse energy acquisition method by using the energy mapping relationship obtained in S4.