Automated Quality Assurance of OAR Contouring for Lung Cancer Based on Segmentation With Deep Active Learning

Automated Quality Assurance of OAR Contouring for Lung Cancer Based on Segmentation With Deep Active Learning

Purpose: Ensuring high-quality data for clinical trials in radiotherapy requires the generation of contours that comply with protocol definitions. The current workflow includes a manual review of the submitted contours, which is time-consuming and subjective. In this study, we developed an automated...

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Bibliographic Details
Main Authors: Kuo Men, Huaizhi Geng, Tithi Biswas, Zhongxing Liao, Ying Xiao
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-07-01
Series:Frontiers in Oncology
Subjects:
quality assurance
OAR contouring
radiotherapy
deep active learning
clinical trial
Online Access:https://www.frontiersin.org/article/10.3389/fonc.2020.00986/full

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