Invention Grant
- Patent Title: Neural network-based corrector for photon counting detectors
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Application No.: US16770675Application Date: 2018-12-07
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Publication No.: US11448778B2Publication Date: 2022-09-20
- Inventor: Ge Wang , Ruibin Feng , David Rundle
- Applicant: RENSSELAER POLYTECHNIC INSTITUTE
- Applicant Address: US NY Troy
- Assignee: RENSSELAER POLYTECHNIC INSTITUTE
- Current Assignee: RENSSELAER POLYTECHNIC INSTITUTE
- Current Assignee Address: US NY Troy
- Agency: Murtha Cullina LLP
- Agent Anthony P. Gangemi
- International Application: PCT/US2018/064468 WO 20181207
- International Announcement: WO2019/113440 WO 20190613
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G01T1/17 ; G01T1/18 ; G06T7/00 ; A61B6/00

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.
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