References

Clinical validation of a deep-learning segmentation software in head and neck: an early analysis in a developing radiation oncology center

10.3390/ijerph19159057 · 2022 · External reference

Deep learning-based segmentation of head and neck organs-at-risk with clinical partially labeled data

10.3390/e24111661 · 2022 · External reference

Automated delineation of head and neck organs at risk using synthetic MRI-aided mask scoring regional convolutional neural network

10.1002/mp.15146 · 2021 · External reference

10.1109/iceccme62383.2024.10797214

10.1109/iceccme62383.2024.10797214 · External reference

Variations in the contouring of organs at risk: test case from a patient with oropharyngeal cancer

10.1016/j.ijrobp.2010.10.019 · 2012 · External reference

CT-based delineation of organs at risk in the head and neck region: DAHANCA, EORTC, GORTEC, HKNPCSG, NCIC CTG, NCRI, NRG oncology and TROG consensus guidelines

10.1016/j.radonc.2015.07.041 · 2015 · External reference

Defining truth in contouring: a study of automatic atlas-based lymph node segmentation (LNS) for head and neck cancer (HNC)

10.1016/j.ijrobp.2009.07.892 · 2009 · External reference

Deep learning for elective neck delineation: more consistent and time efficient

10.1016/j.radonc.2020.10.007 · 2020 · External reference

Multicentre evaluation of deep learning CT autosegmentation of the head and neck region for radiotherapy

10.1038/s41746-025-01624-z · 2025 · External reference

Inter-observer variability in radiotherapy contouring with the use of autocontouring software: a systematic review

2026 · External reference

Multi-atlas segmentation of biomedical images: a survey

10.1016/j.media.2015.06.012 · 2015 · External reference

Automated contouring and planning in radiation therapy: what is ‘clinically acceptable’?

2023 · External reference

Deep learning-based two-step organs at risk auto-segmentation model for brachytherapy planning in parotid gland carcinoma

10.5114/jcb.2022.123972 · 2022 · External reference

Validation of clinical acceptability of deep-learning-based automated segmentation of organs-at-risk for head-and-neck radiotherapy treatment planning

10.3389/fonc.2023.1137803 · 2023 · External reference

Evaluating the effectiveness of deep learning contouring across multiple radiotherapy Centres

10.1016/j.phro.2022.11.003 · 2022 · External reference

Training and validation of deep learning-based auto-segmentation models for lung stereotactic ablative radiotherapy using retrospective radiotherapy planning contours

10.3389/fonc.2021.626499 · 2021 · External reference

Identifying patients who may benefit from adaptive radiotherapy: does the literature on anatomic and dosimetric changes in head and neck organs at risk during radiotherapy provide information to help?

10.1016/j.radonc.2015.05.018 · 2015 · External reference

Predictive modeling using shape statistics for interpretable and robust quality assurance of automated contours in radiation treatment planning HHS public access

2023 · External reference

Geometric, dosimetric and psychometric evaluation of three commercial AI software solutions for OAR auto-segmentation in head and neck radiotherapy

2025 · External reference

Improving automatic delineation for head and neck organs at risk by deep learning contouring

10.1016/j.radonc.2019.09.022 · 2020 · External reference

Implementation of a commercial deep learning-based auto segmentation software in radiotherapy: evaluation of effectiveness and impact on workflow

10.3390/life12122088 · 2022 · External reference

Metrics to evaluate the performance of auto-segmentation for radiation treatment planning: a critical review

10.1016/j.radonc.2021.05.003 · 2021 · External reference

Evaluation of measures for assessing time-saving of automatic organ-at-risk segmentation in radiotherapy

10.1016/j.phro.2019.12.001 · 2020 · External reference

Comparing deep learning-based auto-segmentation of organs at risk and clinical target volumes to expert inter-observer variability in radiotherapy planning

10.1016/j.radonc.2019.10.019 · 2020 · External reference

How smart is artificial intelligence in organs delineation? Testing a CE and FDA-approved deep-learning tool using multiple expert contours delineated on planning CT images

10.3389/fonc.2023.1089807 · 2023 · External reference

Deep learning-based delineation of head and neck organs at risk: geometric and Dosimetric evaluation

10.1016/j.ijrobp.2019.02.040 · 2019 · External reference

Multi-atlas auto-segmentation for head and neck OARs: accuracy and time efficiency

10.1016/s0167-8140(18)30734-5 · 2018 · External reference

Künstliche Intelligenz in der Strahlentherapie

10.1007/s12312-024-01353-6 · 2024 · External reference