Invention Grant
- Patent Title: System and method for determining a trained neural network model for scattering correction
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Application No.: US16042536Application Date: 2018-07-23
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Publication No.: US10803555B2Publication Date: 2020-10-13
- Inventor: Yanli Song , Xin Zhou , Xiaodan Xing , Gang Chen , Qiang Li
- Applicant: SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD.
- Applicant Address: CN Shanghai
- Assignee: SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD.
- Current Assignee: SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD.
- Current Assignee Address: CN Shanghai
- Agency: Metis IP LLC
- Priority: com.zzzhc.datahub.patent.etl.us.BibliographicData$PriorityClaim@1ed4f1d7 com.zzzhc.datahub.patent.etl.us.BibliographicData$PriorityClaim@289c0ab4
- Main IPC: G06T5/00
- IPC: G06T5/00 ; G06N3/08 ; G06N3/04 ; A61B6/00

Abstract:
A method for generating a trained neural network model for scanning correction corresponding to one or more imaging parameters is provided. The trained neural network model may be trained using training data. The training data may include at least one first set of training data. The first set of training data may be generated according to a process for generating the first set of training data. The process may include obtaining a first image and a second image corresponding to the one or more imaging parameters. The second image may include less scattering noises than the first image. The process may further include determine the first set of training data based on the first image and the second image.
Public/Granted literature
- US20190066268A1 SYSTEM AND METHOD FOR DETERMINING A TRAINED NEURAL NETWORK MODEL FOR SCATTERING CORRECTION Public/Granted day:2019-02-28
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