A medical image processing device comprising: a first position acquirer configured to acquire, as first positions, target positions in a plurality of first images that are transparent images at a plurality of points in time at which a patient is imaged, wherein each of the plurality of first images is a DRR image created on the basis of a three-dimensional CT image captured at the time of treatment planning; a first converter configured to convert the first positions in the plurality of first images to second positions, using a transformation matrix set on the basis of movement over time of the first positions, wherein a trajectory of the movement of the first positions in the first images is oval and the transformation matrix is determined so that the trajectory becomes an accurate circle; a first likelihood image generator configured to generate a first likelihood image showing a distribution of likelihood indicating a probability of the target position corresponding to a second position on the basis of that position, wherein a part with high luminance is a part in which the target position is highly likely to be present; and a learner configured to output a model which uses the plurality of first images and the corresponding first likelihood images as training data, and upon receiving part or all of a transparent image, derives a second likelihood image showing a distribution of likelihood indicating probability of the target in the part or all of the transparent image corresponding to the second positions, wherein the received transparent image is an image captured during radiation of a treatment beam to the patient. a first position acquirer configured to acquire, as first positions, target positions in a plurality of first images that are transparent images at a plurality of points in time at which a patient is imaged, wherein each of the plurality of first images is a DRR image created on the basis of a three-dimensional CT image captured at the time of treatment planning; a first converter configured to convert the first positions in the plurality of first images to second positions, using a transformation matrix set on the basis of movement over time of the first positions, wherein a trajectory of the movement of the first positions in the first images is oval and the transformation matrix is determined so that the trajectory becomes an accurate circle; a first likelihood image generator configured to generate a first likelihood image showing a distribution of likelihood indicating a probability of the target position corresponding to a second position on the basis of that position, wherein a part with high luminance is a part in which the target position is highly likely to be present; and a learner configured to output a model which uses the plurality of first images and the corresponding first likelihood images as training data, and upon receiving part or all of a transparent image, derives a second likelihood image showing a distribution of likelihood indicating probability of the target in the part or all of the transparent image corresponding to the second positions, wherein the received transparent image is an image captured during radiation of a treatment beam to the patient. <EOS>