Invention Grant
- Patent Title: Cone-beam CT image enhancement using generative adversarial networks
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Application No.: US16044245Application Date: 2018-07-24
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Publication No.: US11501438B2Publication Date: 2022-11-15
- Inventor: Jiaofeng Xu , 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.
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06T7/00 ; G06N3/08 ; G06F17/18

Abstract:
Techniques for generating an enhanced cone-beam computed tomography (CBCT) image using a trained model are provided. A CBCT image of a subject is received. a synthetic computed tomography (sCT) image corresponding to the CBCT image is generated, using a generative model. The generative model is trained in a generative adversarial network (GAN). The generative model is further trained to process the CBCT image as an input and provide the sCT image as an output. The sCT image is presented for medical analysis of the subject.
Public/Granted literature
- US20190333219A1 CONE-BEAM CT IMAGE ENHANCEMENT USING GENERATIVE ADVERSARIAL NETWORKS Public/Granted day:2019-10-31
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