학술논문
Assessment of deep learning-based auto-contouring on interobserver consistency in target volume and organs-at-risk delineation for breast cancer: Implications for RTQA program in a multi-institutional study
Document Type
Article
Author
Choi, M.S.; Chang, J.S.; Chun, J.; Kim, J.S.; Kim, Y.B.; Kim, K.; Lee, E.M.; Kim, J.H.; Kim, T.H.; Kim, S.; Cha, H.; Cho, O.; Choi, J.H.; Kim, M.; Kim, J.; Kim, T.G.; Yeo, S.-G.; Chang, A.R.; Ahn, S.-J.; Choi, J.; Kang, K.M.; Kwon, J.; Koo, T.; Kim, M.Y.; Choi, S.H.; Jeong, B.K.; Jo, I.Y.; Lee, H.; Kim, N.; Park, H.J.; Im, J.H.; Lee, S.-W.; Cho, Y.; Lee, S.Y.; Jang, B.-S.; Chang, J.H.; Shin, K.H.
Source
In: Breast . (Breast, February 2024, 73)
Subject
Language
English
ISSN
15323080
09609776
09609776