Research graph
References from Quantifying manual editing time in autocontouring via audit log analysis. Local targets link to admitted publications; unresolved targets remain external evidence.
A clinical evaluation of the performance of five commercial artificial intelligence contouring systems for radiotherapy
2023 · External reference
Artificial intelligence−based autosegmentation: advantages in delineation, absorbed dose-distribution, and logistics
2024 · External reference
Guidance on selecting and evaluating AI auto-segmentation systems in clinical radiotherapy: insights from a six-vendor analysis
10.1007/s13246-024-01513-x · 2025 · External reference
Royal College of Radiologists guidance statements on the use of auto-contouring in radiotherapy
10.1016/j.clon.2025.104004 · 2026 · External reference
Real world AI-driven segmentation: efficiency gains and workflow challenges in radiotherapy
10.1016/j.radonc.2025.110977 · 2025 · External reference
Clinical evaluation of deep learning and atlas-based auto- segmentation for critical organs at risk in radiation therapy
10.1002/jmrs.618 · 2022 · External reference
Atlas-based automatic segmentation of head and neck organs at risk and nodal target volumes : a clinical validation
10.1186/1748-717x-8-154 · 2013 · External reference
Feasibility of automated AI-based contouring and stable radiomic feature assessment by HyperSight-CBCT imaging for adaptive high-precision radiotherapy of prostate cancer
10.1038/s41598-026-46359-3 · 2026 · External reference
A comprehensive multifaceted technical evaluation framework for implementation of auto-segmentation models in radiotherapy
10.1038/s43856-025-01048-6 · 2025 · External reference
Benefits of deep learning for delineation of organs at risk in head and neck cancer
10.1016/j.radonc.2019.05.010 · 2019 · External reference
Deep learning-assisted interactive contouring of lung cancer: impact on contouring time and consistency
10.1016/j.radonc.2024.110500 · 2024 · External reference
Potential of E-learning interventions and artificial intelligence – assisted contouring skills in radiotherapy : the ELAISA study
2024 · External reference
Observer variation in target volume delineation of lung cancer related to radiation oncologist – computer interaction : a big brother ’ evaluation
10.1016/j.radonc.2005.09.017 · 2005 · 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
Novel autosegmentation spatial similarity metrics capture the time required to correct segmentations better than traditional metrics in a thoracic cavity segmentation workflow
10.1007/s10278-021-00460-3 · 2021 · External reference
Clinical implementation of deep learning contour autosegmentation for prostate radiotherapy
10.1016/j.radonc.2021.02.040 · 2021 · External reference
Real-world analysis of manual editing of deep learning contouring in the thorax region
10.1016/j.phro.2022.04.008 · 2022 · External reference
Deep learning based automatic contour refinement for inaccurate auto-segmentation in MR-guided adaptive radiotherapy
2024 · External reference
Delineation of organs at risk in radiotherapy and perspectives
2025 · External reference
Review using event logs to observe interactions with electronic health records : an updated scoping review shows increasing use of vendor-derived measures
10.1093/jamia/ocac177 · 2023 · External reference
Multicenter comparison of measures for quantitative evaluation of contouring in radiotherapy
10.1016/j.phro.2022.11.009 · 2022 · External reference
On the evaluation of auto-contouring in radiotherapy
2021 · External reference
User’s guide to correlation coefficients
10.1016/j.tjem.2018.08.001 · 2018 · External reference
Contouring in transition: perceptions of AI-based autocontouring by radiation oncologists and medical physicists in German-speaking countries
10.1007/s00066-025-02403-1 · 2025 · External reference
Evaluating the effectiveness of deep learning contouring across multiple radiotherapy centres
10.1016/j.phro.2022.11.003 · 2022 · External reference
