Three‐dimensional deep neural network for automatic delineation of cervical cancer in planning computed tomography images-Reference-Cited by-同舟云学术

Three‐dimensional deep neural network for automatic delineation of cervical cancer in planning computed tomography images

Published:2022-02-22 Issue:4 Volume:23 Page:
ISSN:1526-9914
Container-title:Journal of Applied Clinical Medical Physics
language:en
Short-container-title:J Applied Clin Med Phys

Author:

Ding Yi¹,Chen Zhiran¹²,Wang Ziqi²,Wang Xiaohong¹,Hu Desheng¹,Ma Pingping¹,Ma Chi³,Wei Wei¹,Li Xiangbin¹,Xue Xudong¹,Wang Xiao³

Affiliation:

1. Department of Radiation Oncology Hubei Cancer Hospital TongJi Medical College Huazhong University of Science and Technology Wuhan Hubei China

2. Key Laboratory of Artificial Micro and Nano‐structures of Ministry of Education Center for Theoretical Physics School of Physics and Technology Wuhan University Wuhan China

3. Department of Radiation Oncology Rutgers‐Cancer Institute of New Jersey Rutgers‐Robert Wood Johnson Medical School New Brunswick New Jersey USA

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging,Instrumentation,Radiation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/acm2.13566

Reference30 articles.

1. Evidence for the path to cervical cancer elimination

2. Predictive factors for the sensitivity of radiotherapy and prognosis of esophageal squamous cell carcinoma

3. American Brachytherapy Society consensus guidelines for locally advanced carcinoma of the cervix. Part II: High-dose-rate brachytherapy

4. The impact of dosimetric inadequacy on treatment outcome of nasopharyngeal carcinoma with IMRT

5. The accuracy of drainage network delineation as a function of environmental factors: A case study in Central and Northern Sweden

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