Invention Grant
- Patent Title: Methods and systems for hierarchical machine learning models for medical imaging
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Application No.: US15900386Application Date: 2018-02-20
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Publication No.: US10679753B2Publication Date: 2020-06-09
- Inventor: Christian Fritz Perrey , Nitin Singhal
- Applicant: General Electric Company
- Applicant Address: US NY Schenectady
- Assignee: General Electric Company
- Current Assignee: General Electric Company
- Current Assignee Address: US NY Schenectady
- Priority: com.zzzhc.datahub.patent.etl.us.BibliographicData$PriorityClaim@73512669
- Main IPC: G16H50/20
- IPC: G16H50/20 ; G16H30/20 ; G16H30/40 ; G06N20/00 ; G06N5/00

Abstract:
Systems and methods are provided relating to hierarchical machine learning models to identify an anatomical structure of interest and perform diagnostic procedures for a medical diagnostic imaging system. The systems and methods organize a plurality of models into a hierarchical structure based on anatomical structures. The plurality of models are defined by a machine learning algorithm for diagnostic procedures of one or more of the anatomical structures. The systems and methods receive a medical image, identifying an anatomical structure of interest within the medical image, select at least a first model from the plurality of models based on the anatomical structure of interest, and perform a first diagnostic procedure of the anatomical structure of interest based on the first model.
Public/Granted literature
- US20180240551A1 METHODS AND SYSTEMS FOR HIERARCHICAL MACHINE LEARNING MODELS FOR MEDICAL IMAGING Public/Granted day:2018-08-23
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