| CPC G06F 18/214 (2023.01) [A61B 6/12 (2013.01); A61B 6/463 (2013.01); G06T 7/0012 (2013.01); G06V 10/22 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2207/10116 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30004 (2013.01); G06V 2201/034 (2022.01)] | 12 Claims |
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1. A learning device comprising:
at least one processor,
wherein the processor performs machine learning of a learning model by independently inputting each of a plurality of radiographic images that do not include a surgical tool and a plurality of surgical tool images that include only the surgical tool as training data to the learning model, to construct a trained model for detecting a region of the surgical tool from an input radiographic image, and
wherein the learning model comprises a neural network and the processor further performs the machine learning of the neural network, in which when a radiographic image that does not include the surgical tool is input to the neural network as the training data, a probability of being the region of the surgical tool that is output from the neural network becomes 0 in an entire region of the input radiographic image that does not include the surgical tool, and when a surgical tool image is input to the neural network as the training data, the probability of being the region of the surgical tool that is output from the neural network becomes 1 in the region of the surgical tool in the input surgical tool image.
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