Invention Grant
- Patent Title: Deep learning for arterial analysis and assessment
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Application No.: US16192551Application Date: 2018-11-15
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Publication No.: US10964017B2Publication Date: 2021-03-30
- Inventor: Jed Douglas Pack , Peter Michael Edic , Xin Wang , Xia Li , Prem Venugopal , James Vradenburg Miller
- Applicant: General Electric Company
- Applicant Address: US NY Schenectady
- Assignee: General Electric Company
- Current Assignee: General Electric Company
- Current Assignee Address: US NY Schenectady
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G16H50/20 ; G16H30/40 ; G06N3/08

Abstract:
The present disclosure relates to training one or more neural networks for vascular vessel assessment using synthetic image data for which ground-truth data is known. In certain implementations, the synthetic image data may be based in part, or derived from, clinical image data for which ground-truth data is not known or available. Neural networks trained in this manner may be used to perform one or more of vessel segmentation, decalcification, Hounsfield unit scoring, and/or estimation of a hemodynamic parameter.
Public/Granted literature
- US20200160509A1 DEEP LEARNING FOR ARTERIAL ANALYSIS AND ASSESSMENT Public/Granted day:2020-05-21
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