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Title:
METHOD AND APPARATUS FOR PREDICTING REGION-SPECIFIC CEREBRAL CORTICAL CONTRACTION RATE ON BASIS OF CT IMAGE
Document Type and Number:
WIPO Patent Application WO/2021/045507
Kind Code:
A2
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.

Inventors:
SEONG JUN KYUNG (KR)
SEO SANG WON (KR)
KIM JEONG HUN (KR)
KIM SIHYEON (KR)
Application Number:
PCT/KR2020/011790
Publication Date:
March 11, 2021
Filing Date:
September 02, 2020
Export Citation:
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Assignee:
UNIV KOREA RES & BUS FOUND (KR)
SAMSUNG LIFE PUBLIC WELFARE FOUNDATION (KR)
International Classes:
A61B6/00
Attorney, Agent or Firm:
DAHAI INTERNATIONAL PATENT & LAW FIRM (KR)
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