Abstract: The present invention relates to an apparatus for predicting a region-specific cerebral cortical contraction rate on the basis of a CT image.

Abstract: The method for predicting Alzheimer's disease-related biomarkers according to the present disclosure involves a method executed by one or more processors of a computing device. The method comprises collecting medical images of a subject, preprocessing the collected medical images to generate training data, training a biomarker prediction model using the generated training data and the subject's demographic and clinical information, where the training includes assigning weights to the training data, and predicting Alzheimer's disease-related biomarkers for a patient using the trained biomarker prediction model.

Abstract: Disclosed herein a method of constructing a blood vessel map, the method including: receiving, by a blood vessel map construction apparatus, a TOF image of the object; extracting, by the blood vessel map construction apparatus, a blood vessel stem, a center line of a blood vessel, and features of the center line included in the TOF image, and detecting branch points of the blood vessel based on the extracted blood vessel stem, center line of the blood vessel, and features of the center line; searching, by the blood vessel map construction apparatus, a reference blood vessel image corresponding to the TOF image in consideration of location information or curvature information of the branch points; calculating a similarity between the TOF image and the reference blood vessel image; and registering the TOF image in the blood vessel map based on the similarity.

Abstract: The present invention relates to an apparatus for predicting a region-specific cerebral cortical contraction rate on the basis of a CT image.

Abstract: Disclosed is a hierarchical diagnosis device of brain atrophy based on brain thickness information, including a brain structure modeling unit to generate a grey matter surface mesh and a white matter surface mesh by mesh modeling of multiple Magnetic Resonance Imaging (MRI) images; a brain thickness extraction unit to acquire brain thickness information by collecting and analyzing a distance between corresponding points of the grey matter surface mesh and the white matter surface mesh; a training data generation unit to generate and store multiple training data including the brain thickness information and diagnosis information when diagnosis model training is requested; a diagnosis model training unit to classify and analyze the brain thickness information into groups of a hierarchical structure according to the diagnosis information to acquire feature information for each group, and generate and train hierarchical classifiers based on the hierarchical structure of the groups and the feature information for

Abstract: Disclosed herein a method of constructing a blood vessel map, the method including: receiving, by a blood vessel map construction apparatus, a TOF image of the object; extracting, by the blood vessel map construction apparatus, a blood vessel stem, a center line of a blood vessel, and features of the center line included in the TOF image, and detecting branch points of the blood vessel based on the extracted blood vessel stem, center line of the blood vessel, and features of the center line; searching, by the blood vessel map construction apparatus, a reference blood vessel image corresponding to the TOF image in consideration of location information or curvature information of the branch points; calculating a similarity between the TOF image and the reference blood vessel image; and registering the TOF image in the blood vessel map based on the similarity.

Abstract: The present disclosure relates to exhalation-based lung cancer diagnosis method and system.

Abstract: A biological brain age is calculated by measuring a brain cortex thickness of each region in a brain MRI image of a person to be examined, and comparing the measured brain cortex thickness with normal control group information. A device for calculating the biological brain includes an image information input unit to input an MRI brain image of a person to be examined, a brain age calculation control unit to control a biological brain age calculation operation of the person to be examined based on the MRI brain image, a brain thickness measuring unit to measure a brain cortex thickness of each region in the MRI brain image, and a brain age calculating unit to match the measured brain cortex thickness with a normal range of brain thickness of each age, and calculate a biological brain age of the person to be examined.

Abstract: A biological brain age is calculated by measuring a brain cortex thickness of each region in a brain MRI image of a person to be examined, and comparing the measured brain cortex thickness with normal control group information. A device for calculating the biological brain includes an image information input unit to input an MRI brain image of a person to be examined, a brain age calculation control unit to control a biological brain age calculation operation of the person to be examined based on the MRI brain image, a brain thickness measuring unit to measure a brain cortex thickness of each region in the MRI brain image, and a brain age calculating unit to match the measured brain cortex thickness with a normal range of brain thickness of each age, and calculate a biological brain age of the person to be examined.