Evaluation of deep learning‐based auto‐segmentation algorithms for delineating clinical target volume and organs at risk involving data for 125 cervical cancer patients-Reference-Cited by-同舟云学术

Evaluation of deep learning‐based auto‐segmentation algorithms for delineating clinical target volume and organs at risk involving data for 125 cervical cancer patients

Published:2020-11-25 Issue:12 Volume:21 Page:272-279
ISSN:1526-9914
Container-title:Journal of Applied Clinical Medical Physics
language:en
Short-container-title:J Appl Clin Med Phys

Author:

Wang Zhi¹²,Chang Yankui¹,Peng Zhao¹,Lv Yin²,Shi Weijiong²,Wang Fan²,Pei Xi¹³,Xu X. George¹

Affiliation:

1. Center of Radiological Medical Physics University of Science and Technology of China Hefei China

2. Department of Radiation Oncology First Affiliated Hospital of Anhui Medical University Hefei China

3. Anhui Wisdom Technology Co., Ltd. Hefei Anhui China

Funder

Natural Science Foundation of Anhui Province

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging,Instrumentation,Radiation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/acm2.13097

Reference54 articles.

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4. Variability of Target and Normal Structure Delineation for Breast Cancer Radiotherapy: An RTOG Multi-Institutional and Multiobserver Study

5. Automatic delineation and evaluation of target areas for nasopharyngeal carcinoma;Wu X;Sichuan Med,2015

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