A review of interventions to reduce inter‐observer variability in volume delineation in radiation oncology

SK Vinod, M Min, MG Jameson… - Journal of medical …, 2016 - Wiley Online Library
Introduction Inter‐observer variability (IOV) in target volume and organ‐at‐risk (OAR)
delineation is a source of potential error in radiation therapy treatment. The aims of this study …

Uncertainties in volume delineation in radiation oncology: a systematic review and recommendations for future studies

SK Vinod, MG Jameson, M Min, LC Holloway - Radiotherapy and Oncology, 2016 - Elsevier
Background and purpose Volume delineation is a well-recognised potential source of error
in radiotherapy. Whilst it is important to quantify the degree of interobserver variability (IOV) …

Segmentation of organs‐at‐risks in head and neck CT images using convolutional neural networks

B Ibragimov, L Xing - Medical physics, 2017 - Wiley Online Library
Purpose Accurate segmentation of organs‐at‐risks (OAR s) is the key step for efficient
planning of radiation therapy for head and neck (HaN) cancer treatment. In the work, we …

Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks

K Men, J Dai, Y Li - Medical physics, 2017 - Wiley Online Library
Purpose Delineation of the clinical target volume (CTV) and organs at risk (OAR s) is very
important for radiotherapy but is time‐consuming and prone to inter‐observer variation …

[HTML][HTML] Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring

LV Van Dijk, L Van den Bosch, P Aljabar… - Radiotherapy and …, 2020 - Elsevier
Introduction Adequate head and neck (HN) organ-at-risk (OAR) delineation is crucial for HN
radiotherapy and for investigating the relationships between radiation dose to OARs and …

[HTML][HTML] Segmentation of organs-at-risk in cervical cancer CT images with a convolutional neural network

Z Liu, X Liu, B Xiao, S Wang, Z Miao, Y Sun, F Zhang - Physica Medica, 2020 - Elsevier
Purpose We introduced and evaluated an end-to-end organs-at-risk (OARs) segmentation
model that can provide accurate and consistent OARs segmentation results in much less …

Advances in radiotherapy for head and neck cancer

V Grégoire, JA Langendijk, S Nuyts - Journal of Clinical Oncology, 2015 - ascopubs.org
Over the last few decades, significant improvements have been made in the radiotherapy
(RT) treatment of head and neck malignancies. The progressive introduction of intensity …

Segmentation of the prostate and organs at risk in male pelvic CT images using deep learning

S Kazemifar, A Balagopal, D Nguyen… - Biomedical Physics …, 2018 - iopscience.iop.org
Inter-and intra-observer variation in delineating regions of interest (ROIs) occurs because of
differences in expertise level and preferences of the radiation oncologists. We evaluated the …

Pet-ct–based auto-contouring in non–small-cell lung cancer correlates with pathology and reduces interobserver variability in the delineation of the primary tumor and …

A Van Baardwijk, G Bosmans, L Boersma… - International Journal of …, 2007 - Elsevier
Purpose: To compare source-to-background ratio (SBR)-based PET-CT auto-delineation
with pathology in non–small-cell lung cancer (NSCLC) and to investigate whether auto …

Interobserver variability in organ at risk delineation in head and neck cancer

J van der Veen, A Gulyban, S Willems, F Maes… - Radiation …, 2021 - Springer
Background In radiotherapy inaccuracy in organ at risk (OAR) delineation can impact
treatment plan optimisation and treatment plan evaluation. Brouwer et al. showed significant …