Abstract: Provided is a deep learning based contrast-enhanced (CE) CT image contrast amplifying method and the deep learning based CE CT image contrast amplifying method includes extracting at least one component CT image between a CE component and a non-CE component for an input CE CT image with the input CE CT image as an input to a previously trained deep learning model; and outputting a contrast-amplified CT image with respect to the CE CT image based on the input CE CT image and the at least one extracted component CT image.
Type:
Grant
Filed:
July 20, 2021
Date of Patent:
May 10, 2022
Assignees:
CLARIPI INC., SEOUL NATIONAL UNIVERSITY R&DB FOUNDATION
Inventors:
Jong Hyo Kim, Hyun Sook Park, Tai Chul Park, Chul Kyun Ahn
Abstract: Provided is a method for CT image denoising based on deep learning, and the method for CT image denoising based on deep learning includes: extracting examination information from an input CT image; selecting at least one deep learning model corresponding to the examination information from multiple previously trained deep learning models; and outputting a CT image denoised from the input CT image by feeding the input CT image into the selected at least one deep learning model.
Type:
Grant
Filed:
November 19, 2018
Date of Patent:
January 12, 2021
Assignees:
CLARIPI INC., SEOUL NATIONAL UNIVERSITY R&DB FOUNDATION
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