Research graph
References from Evaluating artificial intelligence versus human-generated contours in the thorax. Local targets link to admitted publications; unresolved targets remain external evidence.
Emphasizing conformal avoidance versus target definition for IMRT planning in head-and-neck cancer
10.1016/j.ijrobp.2009.09.062 · 2010 · External reference
RTOG 0529: a phase 2 evaluation of dose-painted intensity modulated radiation therapy in combination with 5-fluorouracil and mitomycin-C for the reduction of acute morbidity in carcinoma of the anal canal
10.1016/j.ijrobp.2012.09.023 · 2013 · External reference
Uncertainties in volume delineation in radiation oncology: a systematic review and recommendations for future studies
10.1016/j.radonc.2016.09.009 · 2016 · 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
Large scale crowdsourced radiotherapy segmentations across a variety of cancer anatomic sites
10.1038/s41597-023-02062-w · 2023 · External reference
Association between radiotherapy protocol variations and outcome in the CONVERT trial
2022 · External reference
Clinical impact of contouring variability for prostate Cancer tumor boost
10.1016/j.ijrobp.2024.06.007 · 2024 · External reference
Critical impact of radiotherapy protocol compliance and quality in the treatment of advanced head and neck cancer: results from TROG 02.02
10.1200/jco.2009.27.4498 · 2010 · External reference
Use of crowd innovation to develop an artificial intelligence-based solution for radiation therapy targeting
10.1001/jamaoncol.2019.0159 · 2019 · External reference
Automatic segmentation with deep learning in radiotherapy
10.3390/cancers15174389 · 2023 · External reference
Quantitative evaluation of artificial intelligence-based organ segmentation across multiple anatomic sites using 8 commercial software platforms
10.1016/j.prro.2025.06.012 · 2025 · External reference
A clinical evaluation of the performance of five commercial artificial intelligence contouring systems for radiotherapy
10.3389/fonc.2023.1213068 · 2023 · External reference
Evaluating the clinical acceptability of deep learning contours of prostate and organs-at-risk in an automated prostate treatment planning process
10.1002/mp.15525 · 2022 · External reference
Evaluation of measures for assessing time-saving of automatic organ-at-risk segmentation in radiotherapy
2019 · 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
A review of the metrics used to assess auto-contouring systems in radiotherapy
10.1016/j.clon.2023.01.016 · 2023 · External reference
Dosimetric impact of deep learning-based CT auto-segmentation on radiation therapy treatment planning for prostate cancer
10.1186/s13014-022-01985-9 · 2022 · 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
The comparison of percentages in matched samples
10.1093/biomet/37.3-4.256 · 1950 · External reference
Note on the sampling error of the difference between correlated proportions or percentages
10.1007/bf02295996 · 1947 · External reference
Validation of clinical acceptability of an atlas-based segmentation algorithm for the delineation of organs at risk in head and neck cancer
10.1118/1.4927567 · 2015 · 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
Comparative evaluation of autocontouring in clinical practice: a practical method using the Turing test
10.1002/mp.13200 · 2018 · External reference
Inter-observer variability of manual contour delineation of structures in CT
10.1007/s00330-018-5695-5 · 2019 · External reference
Comprehensive quantitative evaluation of variability in magnetic resonance-guided delineation of oropharyngeal gross tumor volumes and high-risk clinical target volumes: an R-IDEAL Stage 0 prospective study
10.1016/j.ijrobp.2022.01.050 · 2022 · External reference
Quality assurance for AI-based applications in radiation therapy
10.1016/j.semradonc.2022.06.011 · 2022 · External reference
