[HTML][HTML] Overview of artificial intelligence-based applications in radiotherapy: Recommendations for implementation and quality assurance
Artificial Intelligence (AI) is currently being introduced into different domains, including
medicine. Specifically in radiation oncology, machine learning models allow automation and …
medicine. Specifically in radiation oncology, machine learning models allow automation and …
Metrics to evaluate the performance of auto-segmentation for radiation treatment planning: A critical review
Advances in artificial intelligence-based methods have led to the development and
publication of numerous systems for auto-segmentation in radiotherapy. These systems …
publication of numerous systems for auto-segmentation in radiotherapy. These systems …
[HTML][HTML] A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy
Background and purpose Delineating organs at risk (OARs) on computed tomography (CT)
images is an essential step in radiation therapy; however, it is notoriously time-consuming …
images is an essential step in radiation therapy; however, it is notoriously time-consuming …
[HTML][HTML] Evaluation of measures for assessing time-saving of automatic organ-at-risk segmentation in radiotherapy
F Vaassen, C Hazelaar, A Vaniqui, M Gooding… - Physics and Imaging in …, 2020 - Elsevier
Background and purpose In radiotherapy, automatic organ-at-risk segmentation algorithms
allow faster delineation times, but clinically relevant contour evaluation remains challenging …
allow faster delineation times, but clinically relevant contour evaluation remains challenging …
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 …
step in radiation therapy planning is to accurately delineate all organs at risk (OARs) to …
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 …
(H&N), which requires a precise spatial description of the target volumes and organs at risk …
[HTML][HTML] Quality assurance for AI-based applications in radiation therapy
Recent advancements in artificial intelligence (AI) in the domain of radiation therapy (RT)
and their integration into modern software-based systems raise new challenges to the …
and their integration into modern software-based systems raise new challenges to the …
Deep learning for segmentation in radiation therapy planning: a review
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 …
influence on the success of radiation therapy. Manual segmentation is a tedious and time …
Automated contouring and planning in radiation therapy: what is 'clinically acceptable'?
Developers and users of artificial-intelligence-based tools for automatic contouring and
treatment planning in radiotherapy are expected to assess clinical acceptability of these …
treatment planning in radiotherapy are expected to assess clinical acceptability of these …
Deep learning application in smart cities: recent development, taxonomy, challenges and research prospects
The purpose of smart city is to enhance the optimal utilization of scarce resources and
improve the resident's quality of live. The smart cities employed Internet of Things (IoT) to …
improve the resident's quality of live. The smart cities employed Internet of Things (IoT) to …