A medical image processing device, comprising: an input means for inputting a brain image of a test subject; a segmentation means for segmenting gray matter tissue by performing a tissue segmentation process on the brain image of the test subject and creating a resultant gray matter tissue segmented image; a memorizing means for saving an image group of gray matter tissues of healthy subjects; an output means for outputting diagnosis support information based on a statistical comparison between the gray matter tissue segmented image of the test subject obtained by the segmentation means and the image group of gray matter tissues of healthy subjects; characterized in that it further comprises a distinguishing means for distinguishing (S27, S31∼S37) between normal and abnormal results of segmentation by the segmentation means, based on a voxel value of the gray matter tissue segmented image of the test subject and a per-voxel statistical value of normal tissue segmentation images for which the tissue segmentation process has been performed normally, wherein the per-voxel statistical value of the normal tissue segmentation images includes an average value and a standard deviation at each voxel position of the normal tissue segmentation images, and the distinguishing means is configured to distinguish between normal and abnormal results of segmentation by the segmentation means by comparing against a predefined threshold value an average, over all voxels of the gray matter tissue segmented image, of absolute Z-scores which are each obtained from the voxel value at a voxel position in the gray matter tissue segmented image and said average value and standard deviation at the same voxel position in the normal tissue segmentation images. an input means for inputting a brain image of a test subject; a segmentation means for segmenting gray matter tissue by performing a tissue segmentation process on the brain image of the test subject and creating a resultant gray matter tissue segmented image; a memorizing means for saving an image group of gray matter tissues of healthy subjects; an output means for outputting diagnosis support information based on a statistical comparison between the gray matter tissue segmented image of the test subject obtained by the segmentation means and the image group of gray matter tissues of healthy subjects; characterized in that it further comprises a distinguishing means for distinguishing (S27, S31∼S37) between normal and abnormal results of segmentation by the segmentation means, based on a voxel value of the gray matter tissue segmented image of the test subject and a per-voxel statistical value of normal tissue segmentation images for which the tissue segmentation process has been performed normally, wherein the per-voxel statistical value of the normal tissue segmentation images includes an average value and a standard deviation at each voxel position of the normal tissue segmentation images, and the distinguishing means is configured to distinguish between normal and abnormal results of segmentation by the segmentation means by comparing against a predefined threshold value an average, over all voxels of the gray matter tissue segmented image, of absolute Z-scores which are each obtained from the voxel value at a voxel position in the gray matter tissue segmented image and said average value and standard deviation at the same voxel position in the normal tissue segmentation images.