Auto‐segmentation of organs at risk for head and neck radiotherapy planning: from atlas‐based to deep learning methods

T Vrtovec, D Močnik, P Strojan, F Pernuš… - Medical …, 2020 - Wiley Online Library
Radiotherapy (RT) is one of the basic treatment modalities for cancer of the head and neck
(H&N), which requires a precise spatial description of the target volumes and organs at risk …

The future of MRI in radiation therapy: Challenges and opportunities for the MR community

RJ Goodburn, MEP Philippens… - Magnetic resonance …, 2022 - Wiley Online Library
Radiation therapy is a major component of cancer treatment pathways worldwide. The main
aim of this treatment is to achieve tumor control through the delivery of ionizing radiation …

[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] Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report

EMC Huijben, ML Terpstra, S Pai, A Thummerer… - Medical image …, 2024 - Elsevier
Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of
radiation to tumors while sparing healthy tissues over multiple days. Computed tomography …

Deep learning vs. atlas-based models for fast auto-segmentation of the masticatory muscles on head and neck CT images

W Chen, Y Li, BA Dyer, X Feng, S Rao, SH Benedict… - Radiation …, 2020 - Springer
Background Impaired function of masticatory muscles will lead to trismus. Routine
delineation of these muscles during planning may improve dose tracking and facilitate dose …

Shape constrained fully convolutional DenseNet with adversarial training for multiorgan segmentation on head and neck CT and low‐field MR images

N Tong, S Gou, S Yang, M Cao, K Sheng - Medical physics, 2019 - Wiley Online Library
Purpose Image‐guided radiotherapy provides images not only for patient positioning but
also for online adaptive radiotherapy. Accurate delineation of organs‐at‐risk (OAR s) on …

[HTML][HTML] External validation of deep learning-based contouring of head and neck organs at risk

EJL Brunenberg, IK Steinseifer… - Physics and imaging in …, 2020 - Elsevier
Background and purpose Head and neck (HN) radiotherapy can benefit from automatic
delineation of tumor and surrounding organs because of the complex anatomy and the …

Cascaded deep learning‐based auto‐segmentation for head and neck cancer patients: organs at risk on T2‐weighted magnetic resonance imaging

JC Korte, N Hardcastle, SP Ng, B Clark, T Kron… - Medical …, 2021 - Wiley Online Library
Purpose To investigate multiple deep learning methods for automated segmentation (auto‐
segmentation) of the parotid glands, submandibular glands, and level II and level III lymph …

Cross‐modality deep learning: contouring of MRI data from annotated CT data only

JP Kieselmann, CD Fuller… - Medical …, 2021 - Wiley Online Library
Purpose Online adaptive radiotherapy would greatly benefit from the development of
reliable auto‐segmentation algorithms for organs‐at‐risk and radiation targets. Current …

Deep learning algorithm performance in contouring head and neck organs at risk: a systematic review and single-arm meta-analysis

P Liu, Y Sun, X Zhao, Y Yan - BioMedical Engineering OnLine, 2023 - Springer
Purpose The contouring of organs at risk (OARs) in head and neck cancer radiation
treatment planning is a crucial, yet repetitive and time-consuming process. Recent studies …