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

Abstract

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.