Art

J-GLOBAL ID：201902294714023216   Reference number：19A2827515

Preliminary Clinical Study of the Differences Between Interobserver Evaluation and Deep Convolutional Neural Network-Based Segmentation of Multiple Organs at Risk in CT Images of Lung Cancer

肺癌のCT画像におけるリスクでの複数臓器の観察者間評価と深部畳込み神経回路網に基づくセグメンテーションの間の差異に関する予備的臨床研究【JST・京大機械翻訳】

Author (5)： Zhu Jinhan (State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China) ,  Liu Yimei (State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China) ,  Zhang Jun (State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China) ,  Wang Yixuan (State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China) ,  Chen Lixin (State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China)
Material： Frontiers in Oncology (Web)
Volume： 9  Page： 627  Publication year： 2019 
JST Material Number： U7089A  ISSN： 2234-943X  Document type： Article
Article type： 原著論文  Country of issue： Switzerland (CHE)  Language： ENGLISH (EN)

Abstract/Point： Background: In this study, pub...

Register(free) or Log In to access     To see more with JDream III (charged).   {{ this.onShowAbsJLink("http://jdream3.com/lp/jglobal/index.html?docNo=19A2827515&from=J-GLOBAL&jstjournalNo=U7089A") }}

Thesaurus term： confidence interval ,  Spinal Cord ,  *neural network (network) ,  similarity ,  Heart ,  *segmentation ,  contouring ,  *lung tumor ,  three dimension ,  *convolution ,  Esophagus ,  convolutional neuralnetwork ,  Digestive System
Semi thesaurus term： 臨床応用 ,  *観測者 ,  *CT画像 , 【Automatic Indexing@JST】

Author keywords (5)： contour variation ,  deep convolutional neural network ,  organs at risk ,  auto-contouring ,  lung cancer

JST classification (1)： Chemistry,biochemistry and pathology of tumors(=neoplasms)  (GE02030N)

Reference (31)：

• Tao CJ, Yi JL, Chen NY, Ren W, Cheng J, Tung S, et al. Multi-subject atlas-based auto-segmentation reduces interobserver variation and improves dosimetric parameter consistency for organs at risk in nasopharyngeal carcinoma: A multi-institution clinical study. Radiother Oncol. (2015) 115:407-11. doi: 10.1016/j.radonc.2015.05.012
• Nelms BE, Tomé WA, Robinson G, Wheeler J. Variations in the contouring of organs at risk: test case from a patient with oropharyngeal cancer. Int J Radiation Oncol Biol Phys. (2012) 82:368-78. doi: 10.1016/j.ijrobp.2010.10.019
• Lin L, Dou Q, Jin YM, Zhou GQ, Tang YQ, Chen WL, et al. Deep learning for automated contouring of primary tumor volumes by MRI for nasopharyngeal carcinoma. Radiology. (2019) 291:677-86. doi: 10.1148/radiol.2019182012
• Chen AM, Chin R, Beron P, Yoshizaki T, Mikaeilian AG, Cao M. Inadequate target volume delineation and local-regional recurrence after intensity-modulated radiotherapy for human papillomavirus-positive oropharynx cancer. Radiother Oncol. (2017) 123:412-8. doi: 10.1016/j.radonc.2017.04.015
• Rosewall T, Bayley AJ, Chung P, Le LW, Xie J, Baxi S, et al. The effect of delineation method and observer variability on bladder dose-volume histograms for prostate intensity modulated radiotherapy. Radiother Oncol. (2011) 101:479-85. doi: 10.1016/j.radonc.2011.06.039

Terms in the title (13)： 肺癌 ,  CT画像 ,  リスク ,  臓器 ,  観察者 ,  評価 ,  深部 ,  畳込み ,  神経回路網 ,  セグメンテーション ,  差異 ,  臨床 ,  研究