[HTML][HTML] Clinically applicable segmentation of head and neck anatomy for radiotherapy: deep learning algorithm development and validation study

S Nikolov, S Blackwell, A Zverovitch, R Mendes… - Journal of medical …, 2021 - jmir.org
Background: Over half a million individuals are diagnosed with head and neck cancer each
year globally. Radiotherapy is an important curative treatment for this disease, but it requires …

Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy

S Nikolov, S Blackwell, A Zverovitch, R Mendes… - arXiv preprint arXiv …, 2018 - arxiv.org
Over half a million individuals are diagnosed with head and neck cancer each year
worldwide. Radiotherapy is an important curative treatment for this disease, but it requires …

Deep learning for segmentation in radiation therapy planning: a review

G Samarasinghe, M Jameson, S Vinod… - Journal of Medical …, 2021 - Wiley Online Library
Segmentation of organs and structures, as either targets or organs‐at‐risk, has a significant
influence on the success of radiation therapy. Manual segmentation is a tedious and time …

Multi-organ segmentation of the head and neck area: an efficient hierarchical neural networks approach

E Tappeiner, S Pröll, M Hönig, PF Raudaschl… - International journal of …, 2019 - Springer
Purpose In radiation therapy, a key step for a successful cancer treatment is image-based
treatment planning. One objective of the planning phase is the fast and accurate …

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 …

AnatomyNet: deep learning for fast and fully automated whole‐volume segmentation of head and neck anatomy

W Zhu, Y Huang, L Zeng, X Chen, Y Liu, Z Qian… - Medical …, 2019 - Wiley Online Library
Purpose Radiation therapy (RT) is a common treatment option for head and neck (HaN)
cancer. An important step involved in RT planning is the delineation of organs‐at‐risks …

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

W van Rooij, M Dahele, HR Brandao… - International Journal of …, 2019 - Elsevier
Purpose Organ-at-risk (OAR) delineation is a key step in treatment planning but can be time
consuming, resource intensive, subject to variability, and dependent on anatomical …

Clinically applicable deep learning framework for organs at risk delineation in CT images

H Tang, X Chen, Y Liu, Z Lu, J You, M Yang… - Nature Machine …, 2019 - nature.com
Radiation therapy is one of the most widely used therapies for cancer treatment. A critical
step in radiation therapy planning is to accurately delineate all organs at risk (OARs) to …

Evaluation of deep learning to augment image-guided radiotherapy for head and neck and prostate cancers

O Oktay, J Nanavati, A Schwaighofer… - JAMA network …, 2020 - jamanetwork.com
Importance Personalized radiotherapy planning depends on high-quality delineation of
target tumors and surrounding organs at risk (OARs). This process puts additional time …

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 …