[HTML][HTML] Automated tumor segmentation in radiotherapy
Autosegmentation of gross tumor volumes holds promise to decrease clinical demand and
to provide consistency across clinicians and institutions for radiation treatment planning …
to provide consistency across clinicians and institutions for radiation treatment planning …
Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy
MHF Savenije, M Maspero, GG Sikkes… - Radiation …, 2020 - Springer
Background Structure delineation is a necessary, yet time-consuming manual procedure in
radiotherapy. Recently, convolutional neural networks have been proposed to speed-up and …
radiotherapy. Recently, convolutional neural networks have been proposed to speed-up and …
[HTML][HTML] Deep learning for automatic target volume segmentation in radiation therapy: a review
Deep learning, a new branch of machine learning algorithm, has emerged as a fast growing
trend in medical imaging and become the state-of-the-art method in various clinical …
trend in medical imaging and become the state-of-the-art method in various clinical …
Clinical implementation of deep learning contour autosegmentation for prostate radiotherapy
E Cha, S Elguindi, I Onochie, D Gorovets… - Radiotherapy and …, 2021 - Elsevier
Background and purpose Artificial intelligence advances have stimulated a new generation
of autosegmentation, however clinical evaluations of these algorithms are lacking. This …
of autosegmentation, however clinical evaluations of these algorithms are lacking. This …
Autosegmentation for thoracic radiation treatment planning: a grand challenge at AAPM 2017
Purpose This report presents the methods and results of the Thoracic Auto‐Segmentation
Challenge organized at the 2017 Annual Meeting of American Association of Physicists in …
Challenge organized at the 2017 Annual Meeting of American Association of Physicists in …
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 …
treatment planning. One objective of the planning phase is the fast and accurate …
Auto‐segmentation of normal and target structures in head and neck CT images: a feature‐driven model‐based approach
Purpose: Intensity modulated radiation therapy (IMRT) allows greater control over dose
distribution, which leads to a decrease in radiation related toxicity. IMRT, however, requires …
distribution, which leads to a decrease in radiation related toxicity. IMRT, however, requires …
Geometric and dosimetric evaluation of atlas based auto-segmentation of cardiac structures in breast cancer patients
Background and purpose Auto-segmentation represents an efficient tool to segment organs
on CT imaging. Primarily used in clinical setting, auto-segmentation plays an increasing role …
on CT imaging. Primarily used in clinical setting, auto-segmentation plays an increasing role …
Abdominal multi-organ auto-segmentation using 3D-patch-based deep convolutional neural network
Segmentation of normal organs is a critical and time-consuming process in radiotherapy.
Auto-segmentation of abdominal organs has been made possible by the advent of the …
Auto-segmentation of abdominal organs has been made possible by the advent of the …
[HTML][HTML] Clinically applicable segmentation of head and neck anatomy for radiotherapy: deep learning algorithm development and validation study
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 …
year globally. Radiotherapy is an important curative treatment for this disease, but it requires …