Invention Grant
- Patent Title: Performance of machine learning models for automatic quantification of coronary artery disease
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Application No.: US16556324Application Date: 2019-08-30
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Publication No.: US11030490B2Publication Date: 2021-06-08
- Inventor: Lucian Mihai Itu , Tiziano Passerini , Thomas Redel , Puneet Sharma
- Applicant: Siemens Healthcare GmbH
- Applicant Address: DE Erlangen
- Assignee: Siemens Healthcare GmbH
- Current Assignee: Siemens Healthcare GmbH
- Current Assignee Address: DE Erlangen
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06T7/00 ; A61B5/00 ; A61B5/02 ; A61B5/026 ; A61B5/318

Abstract:
Systems and methods for retraining a trained machine learning model are provided. One or more input medical images are received. Measures of interest for a primary task and a secondary task are predicted from the one or more input medical images using a trained machine learning model. The predicted measures of interest for the primary task and the secondary task are output. User feedback on the predicted measure of interest for the secondary task is received. The trained machine learning model is retrained for predicting the measures of interest for the primary task and the secondary task based on the user feedback on the output for the secondary task.
Public/Granted literature
- US20210064936A1 Performance of Machine Learning Models for Automatic Quantification of Coronary Artery Disease Public/Granted day:2021-03-04
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