Machine Learning for Patient-Specific Quality Assurance of VMAT: Prediction and Classification Accuracy-Reference-Cited by-同舟云学术

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Machine Learning for Patient-Specific Quality Assurance of VMAT: Prediction and Classification Accuracy

Published:2019-11 Issue:4 Volume:105 Page:893-902
ISSN:0360-3016
Container-title:International Journal of Radiation Oncology*Biology*Physics
language:en
Short-container-title:International Journal of Radiation Oncology*Biology*Physics

Author:

Li Jiaqi,Wang Le,Zhang Xile,Liu Lu,Li Jun,Chan Maria F.,Sui Jing,Yang Ruijie

Funder

National Natural Science Foundation of China

Peking University

NCI P30 Cancer Center Support

Chinese Academy of Science

Publisher

Elsevier BV

Subject

Cancer Research,Radiology, Nuclear Medicine and imaging,Oncology,Radiation

Reference34 articles.

1. Volumetric modulated arc therapy improves dosimetry and reduces treatment time compared to conventional intensity-modulated radiotherapy for locoregional radiotherapy of left-sided breast cancer and internal mammary nodes;Popescu;Int J Radiat Oncol Biol Phys,2010

2. Volumetric modulation arc radiotherapy with flattening filter-free beams compared with static gantry IMRT and 3D conformal radiotherapy for advanced esophageal cancer: A feasibility study;Nicolini;Int J Radiat Oncol Biol Phys,2012

3. A closer look at RapidArc® radiosurgery plans using very small fields;Fog;Phys Med Biol,2011

4. Impact of the calculation resolution of AAA for small fields and RapidArc treatment plans;Ong;Med Phys,2011

5. Implementing RapidArc into clinical routine: A comprehensive program from machine QA to TPS validation and patient QA;Van Esch;Med Phys,2011

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1. Deep learning for patient-specific quality assurance of volumetric modulated arc therapy: Prediction accuracy and cost-sensitive classification performance;Physica Medica;2024-09

2. Quantified difference of the collapsed cone convolution (CCC) and Monte Carlo (MC) algorithms based on DVH and gamma analysis for cervical cancer radiation therapy;Applied Radiation and Isotopes;2024-08

3. Forecasting model for qualitative prediction of the results of patient-specific quality assurance based on planning and complexity metrics and their interrelations. Pilot study;Reports of Practical Oncology and Radiotherapy;2024-07-22

4. Generating 3D images of VMAT plans for predictive models and activation maps associated with plan deliverability;Medical Physics;2024-07-08

5. The impact of plan complexity on calculation and measurement-based pre-treatment verifications for sliding-window intensity-modulated radiotherapy;Physics and Imaging in Radiation Oncology;2024-07

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