Automatic segmentation of nasopharyngeal carcinoma on CT images using efficient UNet‐2.5D ensemble with semi‐supervised pretext task pretraining

Automatic segmentation of nasopharyngeal carcinoma on CT images using efficient UNet‐2.5D ensemble with semi‐supervised pretext task pretraining

Nasopharyngeal carcinoma (NPC) is primarily treated with radiation therapy. Accurate delineation of target volumes and organs at risk is important. However, manual delineation is time-consuming, variable, and subjective depending on the experience of the radiation oncologist. This work explores the...

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Bibliographic Details
Main Authors: Jansen Keith L. Domoguen, Jen-Jen A. Manuel, Johanna Patricia A. Cañal, Prospero C. Naval
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-11-01
Series:Frontiers in Oncology
Subjects:
nasopharyngeal carcinoma
automatic volume segmentation
deep learning
radiotherapy
semi-supervised learning
pretext tasks
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.980312/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2022.980312/full

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