Neural network-based corrector for photon counting detectors
AssigneeRensselaer Polytechnic Institute
InventorsGe Wang, Ruibin Feng, David Rundle
Life of this patent
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Abstract
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.
Claims27
A method for photon count correction, the method comprising:
- receiving, by a trained artificial neural network (ANN), a detected photon count from a photon counting detector, the detected photon count corresponding to an attenuated energy spectrum, the attenuated energy spectrum related to characteristics of an imaging object and based, at least in part, on an incident energy spectrum;
- training the ANN using training pairs including the detected photon count and a corresponding actual photon count, and using training circuitry, which includes an x-ray source module, an attenuator module, a photon generator module, a pulse generator module, a signal generator module, and a signal detector module, wherein the pulse generator module is configured to receive energies and corresponding arrival times of photons from the photon generator module, and output a corresponding pulse height of each of the photons to the signal generator module;
- and
- correcting, by the trained ANN, the detected photon count to produce a corrected photon count.
A photon count correction system comprising:
- a trained artificial neural network (ANN) configured to receive a detected photon count from a photon counting detector, the detected photon count corresponding to an attenuated energy spectrum, the attenuated energy spectrum related to characteristics of an imaging object and based, at least in part, on an incident energy spectrum,
- the trained ANN further configured to correct the detected photon count to produce a corrected photon count;
- wherein the ANN is trained using training pairs including the detected photon count and a corresponding actual photon count, and using training circuitry, which includes an x-ray source module, an attenuator module, a photon generator module, a pulse generator module, a signal generator module, and a signal detector module, wherein the pulse generator module is configured to receive energies and corresponding arrival times of photons from the photon generator module, and output a corresponding pulse height of each of the photons to the signal generator module.
A method for photon count correction, the method comprising:
- receiving, by a trained artificial neural network (ANN), a detected photon count from a photon counting detector, the detected photon count corresponding to an attenuated energy spectrum, the attenuated energy spectrum related to characteristics of an imaging object and based, at least in part, on an incident energy spectrum;
- training the ANN using training pairs including the detected photon count and a corresponding actual photon count, and using parameters including at least one of a trigger threshold and spectrum thresholds, the trigger threshold is greater than or equal to a maximum energy of an x-ray energy spectrum output from the x-ray source, and the spectrum thresholds are less than the maximum energy of the x-ray energy spectrum output from the x-ray source;
- and
- correcting, by the trained ANN, the detected photon count to produce a corrected photon count.
Dependencies are inferred from the claim text.