Corrigendum to ‘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’ [The Breast 73 (2024) 103599]

Min Seo Choi(Yonsei University), Yong Bae Kim(Yonsei University), Tae Gyu Kim(Samsung (South Korea)), Kyubo Kim(Hallym University), Ji Hyun Chang(Seoul National University Hospital), Jin Hwa Choi(The Catholic University of Korea Incheon St. Mary's Hospital), In Young Jo(Soonchunhyang University Hospital Seoul), Seo Hee Choi(Yonsei University), Bae Kwon Jeong(Gyeongsang National University), Jung Ho Im(Yonsei University), Ah Ram Chang(Soonchunhyang University), Seung‐Gu Yeo(Soonchunhyang University Hospital Seoul), Sung‐Ja Ahn(Gyeongsang National University Hospital), Oyeon Cho(Chung-Ang University Hospital), Hyejung Cha(Yonsei University), Kyung Hwan Shin(Seoul National University), Bum‐Sup Jang(Seoul National University), Jee Suk Chang(Yonsei University), Jaehee Chun(Yonsei University), Taeryool Koo(Seoul National University), Sea-Won Lee(Jeonbuk National University Hospital), Yeona Cho(Gangnam Severance Hospital), Sun Young Lee(Jeonbuk National University Hospital), Tae Hyung Kim(Yonsei University), Jin Hee Kim(Yonsei University), Sungmin Kim(Dankook University Hospital), Myungsoo Kim(Kyungpook National University Hospital), Mi Young Kim(Kyungpook National University Hospital), Jinhyun Choi(Chungnam National University), Hae Jin Park(Hanyang University), Juree Kim(Yonsei University), Hyebin Lee(Kangbuk Samsung Hospital), Eung Man Lee(Ewha Womans University), Ki Mun Kang(Changwon National University), Jeanny Kwon(Chungnam National University Hospital), Nalee Kim(Yonsei University)
The Breast
December 30, 2023
Cited by 0


Related Papers