| CPC G06T 7/0012 (2013.01) [G06T 5/77 (2024.01); G06T 7/11 (2017.01); G06V 10/751 (2022.01); G06V 10/764 (2022.01); G06V 10/771 (2022.01); G06V 10/7715 (2022.01); G06V 10/82 (2022.01); G06V 10/993 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2207/10024 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30041 (2013.01); G06T 2207/30096 (2013.01); G06T 2207/30168 (2013.01); G06V 2201/03 (2022.01)] | 20 Claims |
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1. A computer implemented method of re-classifying a clinically significant feature of a medical image as an artifact, comprising:
feeding a target medical image captured by a specific medical imaging sensor at a specific setup into a machine learning model;
obtaining a target feature map as an outcome of the machine learning model,
wherein the target feature map includes target features classified as clinically significant by the machine learning model;
analyzing the target feature map with respect to at least one sample feature map obtained as an outcome of the machine learning model fed a sample medical image captured by at least one of: the same specific medical imaging sensor and the same specific setup,
wherein the at least one sample feature map includes sample features classified as clinically significant by the machine learning model;
identifying at least one target feature depicted in the target feature map having attributes matching at least one sample feature depicted in the at least one sample feature map; and
re-classifying as an artifact, the identified at least one target feature depicted in the target medical image and classified as clinically significant by the machine learning model.
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