Convolutional neural network in nasopharyngeal carcinoma: how good is automatic delineation for primary tumor on a non-contrast-enhanced fat-suppressed T2-weighted MRI?-Reference-Cited by-同舟云学术

Convolutional neural network in nasopharyngeal carcinoma: how good is automatic delineation for primary tumor on a non-contrast-enhanced fat-suppressed T2-weighted MRI?

Published:2021-02-05 Issue: Volume: Page:
ISSN:1867-1071
Container-title:Japanese Journal of Radiology
language:en
Short-container-title:Jpn J Radiol

Author:

Wong Lun M.,Ai Qi Yong H.^ORCID,Mo Frankie K. F.,Poon Darren M. C.,King Ann D.

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging

Link

http://link.springer.com/content/pdf/10.1007/s11604-021-01092-x.pdf

Reference32 articles.

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3. Li J, Huang S, Jiang X, Ouyang B, Han F, Liu S, et al. Local failure patterns for patients with nasopharyngeal carcinoma after intensity-modulated radiotherapy. Radiat Oncol. 2014;9(1):87. https://doi.org/10.1186/1748-717X-9-87.

4. He YX, Wang Y, Cao PF, Shen LF, Zhao YJ, Zhang ZJ, et al. Prognostic value and predictive threshold of tumor volume for patients with locally advanced nasopharyngeal carcinoma receiving intensity-modulated radiotherapy. Chin J Cancer. 2016;35(1):96. https://doi.org/10.1186/s40880-016-0159-2.

5. Feng M, Wang W, Fan Z, Fu B, Li J, Zhang S, et al. Tumor volume is an independent prognostic indicator of local control in nasopharyngeal carcinoma patients treated with intensity-modulated radiotherapy. Radiat Oncol. 2013;8(1):208. https://doi.org/10.1186/1748-717X-8-208.

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