US 12,223,431 B2
Inverse neural network for particle detection in a solid-state-devices
Srutarshi Banerjee, Chicago, IL (US); and Miesher Rodrigues, Buffalo Grove, IL (US)
Assigned to Siemens Medical Solutions USA, Inc., Malvern, PA (US)
Filed by Siemens Medical Solutions USA, Inc., Malvern, PA (US)
Filed on Apr. 16, 2020, as Appl. No. 16/850,306.
Claims priority of provisional application 62/927,983, filed on Oct. 30, 2019.
Prior Publication US 2021/0133589 A1, May 6, 2021
Int. Cl. G06N 3/088 (2023.01); G01T 1/16 (2006.01); G06N 3/045 (2023.01)
CPC G06N 3/088 (2013.01) [G06N 3/045 (2023.01); G01T 1/16 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A method of detecting incident radiation with a solid-state detector, the method comprising:
measuring a first signal by the solid-state detector, the first signal generated in response to the incident radiation being received by the solid-state detector;
inputting the measured first signal into a discriminator network configured to output a position and an energy level when input a measured signal from the solid-state detector, wherein the discriminator network is trained using a generative adversarial process as part of a generative adversarial network comprising the discriminator network and a generator network, wherein the generator network is a forward model that uses a position of an interaction and a number of charges to generate signal data, wherein the discriminator network is adversarially trained by inputting either the generated signal data or measured signal data and generating an estimated position and energy level;
determining, by the discriminator network, a first position on the solid-state detector and a first energy level of the incident radiation on the solid-state detector from the measured first signal; and
generating an image from the first position and the first energy level.