Medical image processing device, method of operating medical image processing device, non-transitory computer readable medium, and endoscope system

A method of operating a medical image processing device, comprising:

• a step of acquiring a medical image in which a subject is imaged;
• a step of classifying a region of the subject in the medical image into a first region or a second region;
• a step of detecting a region of interest from the medical image using a first trained model obtained from machine learning with a first data set including data of the first region and data of the second region, with regard to the medical image of which the region of the subject is classified into the first region;
• and
• a step of detecting a region of interest from the medical image using a second trained model obtained from machine learning with a second data set including the data of the second region, with regard to the medical image of which the region of the subject is classified into the second region,
• wherein the first data set includes relatively more data of the first region compared to data of the second region.

A non-transitory computer readable medium for storing a computer-executable program, the computer-executable program causing a computer to execute:

• processing for acquiring a medical image in which a subject is imaged;
• processing for classifying a region of the subject in the medical image into a first region or a second region;
• processing for detecting a region of interest from the medical image using a first trained model obtained from machine learning with a first data set including data of the first region and data of the second region, with regard to the medical image of which the region of the subject is classified into the first region;
• and
• processing for detecting a region of interest from the medical image using a second trained model obtained from machine learning with a second data set including the data of the second region, with regard to the medical image of which the region of the subject is classified into the second region,
• wherein the first data set includes relatively more data of the first region compared to data of the second region.