A 2D–3D hybrid convolutional neural network for lung lobe auto-segmentation on standard slice thickness computed tomography of patients receiving radiotherapy

A 2D–3D hybrid convolutional neural network for lung lobe auto-segmentation on standard slice thickness computed tomography of patients receiving radiotherapy

Abstract Background Accurate segmentation of lung lobe on routine computed tomography (CT) images of locally advanced stage lung cancer patients undergoing radiotherapy can help radiation oncologists to implement lobar-level treatment planning, dose assessment and efficacy prediction. We aim to esta...

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Bibliographic Details
Main Authors: Hengle Gu, Wutian Gan, Chenchen Zhang, Aihui Feng, Hao Wang, Ying Huang, Hua Chen, Yan Shao, Yanhua Duan, Zhiyong Xu
Format: Article
Language:English
Published: BMC 2021-09-01
Series:BioMedical Engineering OnLine
Subjects:
Artificial intelligence
Computed tomography
Automatic segmentation
Lung lobe
Convolutional neural network
Online Access:https://doi.org/10.1186/s12938-021-00932-1

Internet

https://doi.org/10.1186/s12938-021-00932-1

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