Strategies for tackling the class imbalance problem of oropharyngeal primary tumor segmentation on magnetic resonance imaging

Strategies for tackling the class imbalance problem of oropharyngeal primary tumor segmentation on magnetic resonance imaging

Background and purpose: Contouring oropharyngeal primary tumors in radiotherapy is currently done manually which is time-consuming. Autocontouring techniques based on deep learning methods are a desirable alternative, but these methods can render suboptimal results when the structure to segment is c...

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Bibliografiska uppgifter
Huvudupphovsmän: Roque Rodríguez Outeiral, Paula Bos, Hedda J. van der Hulst, Abrahim Al-Mamgani, Bas Jasperse, Rita Simões, Uulke A. van der Heide
Materialtyp: Artikel
Språk:English
Publicerad: Elsevier 2022-07-01
Serie:Physics and Imaging in Radiation Oncology
Ämnen:
Oropharyngeal cancer
Convolutional neural network
Segmentation
Class imbalance, MRI
Two-stage approach
Länkar:http://www.sciencedirect.com/science/article/pii/S2405631622000744

Internet

http://www.sciencedirect.com/science/article/pii/S2405631622000744

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