公开(公告)号：US20220164927A1

公开(公告)日：2022-05-26

申请号：US17535682

申请日：2021-11-25

Applicant: KOREA INSTITUTE OF SCIENCE AND TECHNOLOGY

Inventor： Kihwan CHOI

IPC: G06T5/00 ,  G06N3/04 ,  G06T11/00

Abstract: A method of statistical image restoration for a low-dose CT image using a deep learning, the method includes increasing a number of channels of the low-dose CT image, which is an input image, and decreasing a size of an activation map of the low-dose CT image using an encoder, passing the activation map generated by the encoder to a plurality of residual blocks, and increasing the size of the activation map passed through the residual blocks and generating a denoised result image using a decoder.

公开(公告)号：US20210133572A1

公开(公告)日：2021-05-06

申请号：US17091143

申请日：2020-11-06

Applicant: Korea Institute of Science and Technology

Inventor： Kihwan CHOI ,  Jangho KWON ,  Laehyun KIM

IPC: G06N3/08 ,  G06N3/04 ,  G06N20/20 ,  G06K9/64

Abstract: Disclosed herein is an image preprocessing/analysis apparatus using machine learning-based artificial intelligence. The image preprocessing apparatus includes a computing system, and the computing system includes: a processor; a communication interface configured to receive an input image; and an artificial neural network configured to generate first and second preprocessing conditions through inference on the input image. The processor includes a first preprocessing module configured to generate a first preprocessed image and a second preprocessing module configured to generate a second preprocessed image. The processor is configured to control the first preprocessing module, the second preprocessing module, the artificial neural network, and the communication interface so that the first preprocessed image and the second preprocessed image are transferred to an image analysis module configured to perform image analysis on the input image based on the first preprocessed image and the second preprocessed image.