- Patent Title: Pseudo-CT generation from MR data using a feature regression model
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Application No.: US16354495Application Date: 2019-03-15
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Publication No.: US11234654B2Publication Date: 2022-02-01
- Inventor: Xiao Han
- Applicant: Elekta, Inc.
- Applicant Address: US GA Atlanta
- Assignee: Elekta, Inc.
- Current Assignee: Elekta, Inc.
- Current Assignee Address: US GA Atlanta
- Agency: Schwegman Lundberg & Woessner, P.A.
- Agent Sanjay Agrawal
- Main IPC: A61B5/00
- IPC: A61B5/00 ; G01R33/56 ; G06T5/00 ; G06T11/00 ; G16H30/40 ; G16H30/20 ; G16H50/50 ; A61B5/055 ; A61N5/10 ; A61B90/00

Abstract:
Systems and methods are provided for generating a pseudo-CT prediction model that can be used to generate pseudo-CT images. An exemplary system may include a processor configured to retrieve training data including at least one MR image and at least one CT image for each of a plurality of training subjects. For each training subject, the processor may extract a plurality of features from each image point of the at least one MR image, create a feature vector for each image point based on the extracted features, and extract a CT value from each image point of the at least one CT image. The processor may also generate the pseudo-CT prediction model based on the feature vectors and the CT values of the plurality of training subjects.
Public/Granted literature
- US20190209099A1 PSEUDO-CT GENERATION FROM MR DATA USING A FEATURE REGRESSION MODEL Public/Granted day:2019-07-11
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