Samsung Life Public Welfare Foundation

Korea University Research and Business Foundation

Yonsei University

Jun Kyung Seong

Sang Won Seo

Ji-Eun Lee

Jeong Hun Kim

Changsoo Kim

Duk Lyul Na

Hye Ryun Kim

Woo-Keun Seo

Ha-Na Song

In-Young Baek

Sihyeon Kim

The present invention relates to an apparatus for predicting a region-specific cerebral cortical contraction rate on the basis of a CT image. The present invention may comprise: a deep learning step of a deep learning network learning, by selecting and using CT images of a plurality of patients and segmentation information thereof, a correlation between the CT images and the segmentation information; a feature extraction step of extracting, on the basis of each piece of the segmentation information, semantic feature information corresponding to the CT images; a machine learning step of a machine learning model learning, after a plurality of region-specific cerebral cortical contraction rates corresponding to each piece of the semantic feature information are additionally acquired, a correlation between the semantic feature information and the region-specific cerebral cortical contraction rates; a segmentation step of, when an image to be analyzed is input, acquiring segmentation information corresponding to the image to be analyzed, through the deep learning network; and a prediction step of predicting and reporting, after semantic feature information corresponding to the image to be analyzed is extracted on the basis of the segmentation information, a region-specific cerebral cortical contraction rate corresponding to the semantic feature information through the machine learning model.

Method and apparatus for predicting region-specific cerebral cortical contraction rate on basis of CT image

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.

Device and method for constructing blood vessel map, and computer program for executing said method

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.

Biological brain age calculation device and calculation method therefor

Growing community of inventors

Seoul, South Korea

Jun Kyung Seong