Dai Nippon Printing Co., Ltd.

Hiroshi Matsuda

Tetsutaro Ono

Tomoaki Goto

Seiji Matsuba

Kunihiko Kasahara

A diagnosis support device, which is suitable for comparing different diseases, is provided, along with others. In the diagnosis support device, the input of an MRI brain image of a subject is received, and a shrinkage score, which represents the degree of shrinkage of the brain, is calculated based on the MRI brain image. Subsequently, sites to be compared in the brain are identified. Then, a degree of shrinkage, which represents the degree of shrinkage of each of the identified sites, and a shrinkage ratio, which is the ratio between the degrees of shrinkage of the sites, are calculated, and then compared and displayed.

Medical image display processing method, medical image display processing device, and program

When brain images are inputted through MRI (Magnetic Resonance Imaging) and subjected to image processing to assist the diagnosis of brain diseases, functional and morphological images in an ASL coordinate system are inputted from the head of a subject by an ASL (Arterial Spin Labeling) imaging method using an MRI device. The inputted functional images are subjected to mask processing to extract only the region of cerebral parenchyma, and functional images of only the extracted region of the cerebral parenchyma are thereby produced and displayed to be overlaid on the morphological images. In this manner, a functional image such as a perfusion weighted image of only the region of the cerebral parenchyma can be extracted and displayed overlaid on a morphological image.

Medical image display processing method, device, and program

Input MRI brain images are positioned so as to correct a spatial deviation, gray matter tissues are extracted from these images to effect a first image smoothing, the thus-obtained images are subjected to anatomical standardization, a second image smoothing is effected, the gray level is corrected, brain images after correction are statistically compared with MRI brain images of normal cases, thereby providing the diagnosis result. In this instance, the brain images are automatically checked for input images regarding the resolution dot density and the like, the result of gray matter tissue extraction and the result of anatomical standardization, by which specifications of input images and the like can be confirmed objectively and automatically to make a diagnosis automatically by image processing. Further, an ROI-based analysis is made to provide the analysis result as the diagnosis result.

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Tokorozawa, Japan

Hiroshi Matsuda