Method of generating training data and medical image processing apparatus for deep-learning-based mammography denoising

A method of generating training data for training a machine-learning model, the method comprising:

• obtaining first X-ray image data of a breast of an object;
• generating superimposed image data by superimposing data having a characteristic related to a lesion onto the first X-ray image data;
• and
• outputting the superimposed image data as training data for training a machine-learning model for outputting information based on second X-ray image data.

A medical image processing apparatus comprising:

• processing circuitry configured to perform noise reduction by inputting an input image of a breast into a trained machine-learning model to output an output image in which noise included in the input image is reduced in the output image while leaving a characteristic of a lesion included in the input image undeleted in the output image,
• wherein the trained machine-learning model, for reducing noise in an image while leaving a characteristic of a lesion included in the image undeleted, is generated by training a machine-learning model with a first image as training data for an output side of the machine-learning model, and a second image as training data for an input side of the machine-learning model,
• the first image is generated based on an image of a breast of an object and includes a characteristic of the lesion, and
• the second image includes higher noise than the first image and includes the characteristic of the lesion included in the first image.