Multi-Institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume Using Planning CT and FDG-PET/CT

Multi-Institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume Using Planning CT and FDG-PET/CT

BackgroundThe current clinical workflow for esophageal gross tumor volume (GTV) contouring relies on manual delineation with high labor costs and inter-user variability.PurposeTo validate the clinical applicability of a deep learning multimodality esophageal GTV contouring model, developed at one in...

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Bibliographic Details
Main Authors: Xianghua Ye, Dazhou Guo, Chen-Kan Tseng, Jia Ge, Tsung-Min Hung, Ping-Ching Pai, Yanping Ren, Lu Zheng, Xinli Zhu, Ling Peng, Ying Chen, Xiaohua Chen, Chen-Yu Chou, Danni Chen, Jiaze Yu, Yuzhen Chen, Feiran Jiao, Yi Xin, Lingyun Huang, Guotong Xie, Jing Xiao, Le Lu, Senxiang Yan, Dakai Jin, Tsung-Ying Ho
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-01-01
Series:Frontiers in Oncology
Subjects:
deep learning
PET/CT (18)F-FDG
radiotherapy
segmentation
delineation
esophageal cancer
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2021.785788/full

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https://www.frontiersin.org/articles/10.3389/fonc.2021.785788/full

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