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]

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

doi:10.1016/j.breast.2023.103624

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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]

'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 ' (vol 73 , 103599, 2024)

Choi, Min Seo;
Chang, Jee Suk;
Kim, Kyubo;
Kim, Jin Hee;
Kim, Tae Hyung;
... Park, Hae Jin;
외 31명

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초록

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.

키워드

breast cancer; deep learning; erratum; human; major clinical study; organs at risk; radiation oncology; South Korea

제목: 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]

제목 (타언어): '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 ' (vol 73 , 103599, 2024)

저자: 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

DOI: 10.1016/j.breast.2023.103624

발행일: 2024-04

유형: Correction

저널명: Breast

권: 74

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