Fully automatic and robust segmentation of the clinical target volume for radiotherapy of breast cancer using big data and deep learning

Author:

Men Kuo,Zhang Tao,Chen Xinyuan,Chen Bo,Tang Yu,Wang Shulian,Li Yexiong,Dai Jianrong

Funder

National Natural Science Foundation of China

National Key Projects of Research and Development of China

Publisher

Elsevier BV

Subject

General Physics and Astronomy,Radiology, Nuclear Medicine and imaging,General Medicine,Biophysics

Reference38 articles.

1. Variability of target and normal structure delineation for breast cancer radiotherapy: an RTOG Multi-Institutional and Multiobserver Study;Li;Int J Radiat Oncol Biol Phys,2009

2. Multiinstitutional study on target volume delineation variation in breast radiotherapy in the presence of guidelines;van Mourik;Radiother Oncol,2010

3. Inter-observer and intra-observer reliability for lung cancer target volume delineation in the 4D-CT era;Louie;Int J Radiat Oncol Biol Phys,2009

4. Magnetic resonance imaging for prostate bed radiotherapy planning: an inter- and intra-observer variability study;Barkati;J Med Imag Radiat Oncol,2016

5. Evaluation of multi-atlas-based segmentation of CT scans in prostate cancer radiotherapy;Acosta;IEEE International Symposium on Biomedical Imaging: From Nano To Macro,2011

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