KOREA UNIVERSITY RESEARCH AND BUSINESS FOUNDATION;고려대학교 산학협력단
发明人:
석흥일,최준식,SUK HEUNG IL,CHOI JUN SIK
申请号：
KR1020190143573
公开号：
KR1020200058295A
申请日:
2019.11.11
申请国别(地区):
KR
年份:
2020
代理人:
摘要：
The present invention discloses a method and apparatus for synthesizing deep learning based high magnetic field magnetic resonance images. According to the present invention, a deep learning-based high magnetic field magnetic resonance image synthesis apparatus comprising a processor and a memory connected to the processor, wherein the memory is based on a hostile generating neural network model including a generator and a discriminator, the generator is the author's magnetic field A virtual synthetic high magnetic field magnetic resonance image patch is generated by using a magnetic resonance image patch as an input, and the synthesizer uses the virtual synthetic magnetic field magnetic field image and an actual high magnetic field magnetic resonance image as input to the synthetic high magnetic field magnetic resonance field. Calculate the probability that the image belongs to an actual high magnetic field magnetic resonance image, and a feature extractor calculates a high-dimensional characteristic difference by inputting the virtual synthetic high magnetic field magnetic field image and the actual high magnetic field magnetic resonance image, and the synthetic high magnetic field Parameters of the generator and the discriminator using the total loss reflecting the difference between the magnetic resonance image and the actual high magnetic field magnetic resonance image, the calculated probability, and the perceptual loss according to the high-dimensional characteristic difference. A deep learning based high magnetic field magnetic resonance image synthesis apparatus is provided that stores program instructions executed by the processor to update.본 발명은 딥러닝 기반 고자기장 자기공명영상 합성 방법 및 장치를 개시한다. 본 발명에 따르면, 딥러닝 기반 고자기장 자기공명영상 합성 장치로서, 프로세서 및 상기 프로세서에 연결되는 메모리를 포함하되, 상기 메모리는, 생성기 및 구별기를 포함하는 적대적 생성 신경망 모델 기반으로 상기 생성기가 저자기장 자기공명영상 패치를 입력으로 하여 가상의 합성 고자기장 자기공명영상 패치를 생성하고, 상기 구별기가 상기 가상의 합성 고자기장 자기공명영상 및 실제 고자기장 자기공명영상을 입력으로 하여 상기 합성 고자기장 자기공명영상이 실제 고자기장 자기공명영상에 속할 확률을 계산하고
