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Scalable radiotherapy data curation infrastructure for deep-learning based autosegmentation of organs-at-risk: A case study in head and neck cancer.
Tryggestad E, Anand A, Beltran C, Brooks J, Cimmiyotti J, Grimaldi N, Hodge T, Hunzeker A, Lucido JJ, Laack NN, Momoh R, Moseley DJ, Patel SH, Ridgway A, Seetamsetty S, Shiraishi S, Undahl L, Foote RL. Tryggestad E, et al. Among authors: undahl l. Front Oncol. 2022 Aug 29;12:936134. doi: 10.3389/fonc.2022.936134. eCollection 2022. Front Oncol. 2022. PMID: 36106100 Free PMC article.
Validation of clinical acceptability of deep-learning-based automated segmentation of organs-at-risk for head-and-neck radiotherapy treatment planning.
Lucido JJ, DeWees TA, Leavitt TR, Anand A, Beltran CJ, Brooke MD, Buroker JR, Foote RL, Foss OR, Gleason AM, Hodge TL, Hughes CO, Hunzeker AE, Laack NN, Lenz TK, Livne M, Morigami M, Moseley DJ, Undahl LM, Patel Y, Tryggestad EJ, Walker MZ, Zverovitch A, Patel SH. Lucido JJ, et al. Among authors: undahl lm. Front Oncol. 2023 Apr 6;13:1137803. doi: 10.3389/fonc.2023.1137803. eCollection 2023. Front Oncol. 2023. PMID: 37091160 Free PMC article.