Artificial intelligence in radiation oncology

2020/08/25 by Elizabeth Huynh, Ahmed Hosny, Christian Guthier +11 · 1 voice · 1 citation
Engineering · Medicine · #Advanced X-ray and CT Imaging #Medical Imaging Techniques and Applications #Radiomics and Machine Learning in Medical Imaging

paper · pdf · doi:10.1038/s41571-020-0417-8

crossref issued 2020/08/25 · crossref published 2020/08/25 · crossref published-online 2020/08/25 · openalex publication_date 2020/08/25 · crossref created 2020/08/25 · crossref published-print 2020/12/01 · crossref deposited 2023/10/06 · openalex created_date 2025/10/10 · crossref indexed 2026/07/28 · openalex updated_date 2026/08/01

Citations

• Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012
• European Union Regulations on Algorithmic Decision Making and a “Right to Explanation”
• An Artificial Agent for Robust Image Registration
• Dilated FCN for Multi-Agent 2D/3D Medical Image Registration
• American Association of Physicists in Medicine Task Group 263: Standardizing Nomenclatures in Radiation Oncology
• Dose evaluation of fast synthetic-CT generation using a generative adversarial network for general pelvis MR-only radiotherapy
• Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy
• Cancer treatment and survivorship statistics, 2016

Cited by

• Training and assessing convolutional neural network performance in automatic vascular segmentation using Ga-68 DOTATATE PET/CT

Discussions

• Nice review: Huynh, E., Hosny, A., Guthier, C. et al. Artificial intelligence in radiation oncology. Nat Rev Clin Oncol (2020). doi.org/10.1038/s41571… [bsky, 0 points, 0 comments]