A medical information processing apparatus comprising: a first calculation unit adapted to: calculate a noise intensity from first data acquired during a first scan; calculate a first conversion factor corresponding to a first imaging condition for the first scan based on at least one of following included in the first imaging condition: a number of averages in a k-space, a matrix size in a frequency encoding direction, a matrix size in a phase encoding direction, a number of slice encoding, a factor indicating an unfolding performance during parallel imaging, an acceleration factor of high-speed imaging using compressed sensing, and a number of datasets filled with zero; and calculate a second conversion factor corresponding to a second imaging condition for a second scan different from the first scan based on at least one of following included in the second imaging condition: a number of averages in a k-space, a matrix size in a frequency encoding direction, a matrix size in a phase encoding direction, and a number of slice encoding, the second imaging condition being different form the first imaging condition; and a second calculation unit adapted to calculate a denoising intensity used for a denoising process based on a value obtained by multiplying the noise intensity by a ratio of the second conversion factor to the first conversion factor, the denoising process being applied to data obtained by the second scan. a first calculation unit adapted to: calculate a noise intensity from first data acquired during a first scan; calculate a first conversion factor corresponding to a first imaging condition for the first scan based on at least one of following included in the first imaging condition: a number of averages in a k-space, a matrix size in a frequency encoding direction, a matrix size in a phase encoding direction, a number of slice encoding, a factor indicating an unfolding performance during parallel imaging, an acceleration factor of high-speed imaging using compressed sensing, and a number of datasets filled with zero; and calculate a second conversion factor corresponding to a second imaging condition for a second scan different from the first scan based on at least one of following included in the second imaging condition: a number of averages in a k-space, a matrix size in a frequency encoding direction, a matrix size in a phase encoding direction, and a number of slice encoding, the second imaging condition being different form the first imaging condition; and calculate a noise intensity from first data acquired during a first scan; calculate a first conversion factor corresponding to a first imaging condition for the first scan based on at least one of following included in the first imaging condition: a number of averages in a k-space, a matrix size in a frequency encoding direction, a matrix size in a phase encoding direction, a number of slice encoding, a factor indicating an unfolding performance during parallel imaging, an acceleration factor of high-speed imaging using compressed sensing, and a number of datasets filled with zero; and calculate a second conversion factor corresponding to a second imaging condition for a second scan different from the first scan based on at least one of following included in the second imaging condition: a number of averages in a k-space, a matrix size in a frequency encoding direction, a matrix size in a phase encoding direction, and a number of slice encoding, the second imaging condition being different form the first imaging condition; and a second calculation unit adapted to calculate a denoising intensity used for a denoising process based on a value obtained by multiplying the noise intensity by a ratio of the second conversion factor to the first conversion factor, the denoising process being applied to data obtained by the second scan. <EOS>