인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
The number of CT examination is increasing, and the exposure dose and side effects of contrast agents are also increasing. Recently, Many efforts have been made to solve the problems mentioned by the technological advances of artificial intelligence and deep learning. In this study, Deep learning reconstruction(DLR) AiCE quantitatively compared the imaging characteristics of a conventional filter back projection(FBP) and Hybrid iterative - reconstruction(H-IR) AIDR by concentration difference. The FBP, AIDR, and AiCE were applied to 3 phases(by concentration) in 10 of the 46 patients who underwent liver contrast examination in February 2023. The image quality was evaluated by concentration using Noise, SNR, and CNR. The average rate of change in noise was effective decrease of 67.45 %, 73.98 %, and 20.05 % in the order of AIDR compared to FBP, AiCE compared to FBP, and AiCE compared to AIDR. SNR increased by 144.84 %, 186.50 % and 17.01 %. CNR increased by 142.14 %, 182.38 %, and 16.53 %. Delay(128HU)-AiCE compared to Artery(337HU)- FBP in SNR, Portal(172HU)-AiCE compared to Artery(337HU)-FBP in CNR showed no statistically significant difference. When DLR is applied even at low HU values, improved image results are obtained, so it will be helpful for the use of low concentrations and small amounts of contrast agents.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-151-25-02-092114361
