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
一项多中心研究评估了基于深度学习的自动勾画算法在乳腺癌靶区和危及器官勾画方面观察者间一致性的影响：对放射治疗质量保证（RTQA）项目的启示
期刊:Breast
影响因子:7.9
doi:10.1016/j.breast.2023.103599
Choi, Min Seo; Chang, Jee Suk; Kim, Kyubo; Kim, Jin Hee; Kim, Tae Hyung; Kim, Sungmin; Cha, Hyejung; Cho, Oyeon; Choi, Jin Hwa; Kim, Myungsoo; Kim, Juree; Kim, Tae Gyu; Yeo, Seung-Gu; Chang, Ah Ram; Ahn, Sung-Ja; Choi, Jinhyun; Kang, Ki Mun; Kwon, Jeanny; Koo, Taeryool; Kim, Mi Young; Choi, Seo Hee; Jeong, Bae Kwon; Jang, Bum-Sup; Jo, In Young; Lee, Hyebin; Kim, Nalee; Park, Hae Jin; Im, Jung Ho; Lee, Sea-Won; Cho, Yeona; Lee, Sun Young; Chang, Ji Hyun; Chun, Jaehee; Lee, Eung Man; Kim, Jin Sung; Shin, Kyung Hwan; Kim, Yong Bae
