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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] (The Breast (2024) 73, (S0960977623007257), (10.1016/j.breast.2023.103599))open access
- Authors
- 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
- Issue Date
- Dec-2024
- Publisher
- Churchill Livingstone
- Citation
- Breast
- Indexed
- SCOPUS
- Journal Title
- Breast
- ISSN
- 0960-9776
1532-3080
- Abstract
- The authors apologize for the oversight in presenting incomplete affiliations for author Jin Sung Kim. Jin Sung Kim is affiliated with the Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, Republic of Korea, and Oncosoft Inc., Seoul, Republic of Korea. The authors would like to apologize for any inconvenience caused. © 2023 The Author(s)
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