[HTML][HTML] Deep learning: a review for the radiation oncologist
Introduction: Deep Learning (DL) is a machine learning technique that uses deep neural
networks to create a model. The application areas of deep learning in radiation oncology …
networks to create a model. The application areas of deep learning in radiation oncology …
Deep learning in medical imaging and radiation therapy
The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …
therapy are to (a) summarize what has been achieved to date;(b) identify common and …
Survey on deep learning for radiotherapy
More than 50% of cancer patients are treated with radiotherapy, either exclusively or in
combination with other methods. The planning and delivery of radiotherapy treatment is a …
combination with other methods. The planning and delivery of radiotherapy treatment is a …
Deep learning for radiotherapy outcome prediction using dose data–a review
Artificial intelligence, and in particular deep learning using convolutional neural networks,
has been used extensively for image classification and segmentation, including on medical …
has been used extensively for image classification and segmentation, including on medical …
[HTML][HTML] Machine learning applications in radiation oncology
Abstract Machine learning technology has a growing impact on radiation oncology with an
increasing presence in research and industry. The prevalence of diverse data including 3D …
increasing presence in research and industry. The prevalence of diverse data including 3D …
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 …
Big data and machine learning in radiation oncology: state of the art and future prospects
Precision medicine relies on an increasing amount of heterogeneous data. Advances in
radiation oncology, through the use of CT Scan, dosimetry and imaging performed before …
radiation oncology, through the use of CT Scan, dosimetry and imaging performed before …
The emergence of artificial intelligence within radiation oncology treatment planning
Background: The future of artificial intelligence (AI) heralds unprecedented change for the
field of radiation oncology. Commercial vendors and academic institutions have created AI …
field of radiation oncology. Commercial vendors and academic institutions have created AI …
An image-based deep learning framework for individualising radiotherapy dose: a retrospective analysis of outcome prediction
B Lou, S Doken, T Zhuang, D Wingerter… - The Lancet Digital …, 2019 - thelancet.com
Background Radiotherapy continues to be delivered without consideration of individual
tumour characteristics. To advance towards more precise treatments in radiotherapy, we …
tumour characteristics. To advance towards more precise treatments in radiotherapy, we …
Introduction to machine and deep learning for medical physicists
Recent years have witnessed tremendous growth in the application of machine learning
(ML) and deep learning (DL) techniques in medical physics. Embracing the current big data …
(ML) and deep learning (DL) techniques in medical physics. Embracing the current big data …